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Zhu H, Lai R, Chen W, Lu C, Chachar Z, Lu S, Lin H, Fan L, Hu Y, An Y, Li X, Zhang X, Qi Y. Genetic dissection of maize (Zea maysL.) trace element traits using genome-wide association studies. BMC PLANT BIOLOGY 2023; 23:631. [PMID: 38062375 PMCID: PMC10704835 DOI: 10.1186/s12870-023-04643-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023]
Abstract
Maize (Zea mays L.) is an important food and feed crop worldwide and serves as a a vital source of biological trace elements, which are important breeding targets. In this study, 170 maize materials were used to detect QTNs related to the content of Mn, Fe and Mo in maize grains through two GWAS models, namely MLM_Q + K and MLM_PCA + K. The results identified 87 (Mn), 205 (Fe), and 310 (Mo) QTNs using both methods in the three environments. Considering comprehensive factors such as co-location across multiple environments, strict significance threshold, and phenotypic value in multiple environments, 8 QTNs related to Mn, 10 QTNs related to Fe, and 26 QTNs related to Mo were used to identify 44 superior alleles. Consequently, three cross combinations with higher Mn element, two combinations with higher Fe element, six combinations with higher Mo element, and two combinations with multiple element (Mn/Fe/Mo) were predicted to yield offspring with higher numbers of superior alleles, thereby increasing the likelihood of enriching the corresponding elements. Additionally, the candidate genes identified 100 kb downstream and upstream the QTNs featured function and pathways related to maize elemental transport and accumulation. These results are expected to facilitate the screening and development of high-quality maize varieties enriched with trace elements, establish an important theoretical foundation for molecular marker assisted breeding and contribute to a better understanding of the regulatory network governing trace elements in maize.
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Affiliation(s)
- Hang Zhu
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
- College of Agriculture, Yangtze University, Jingzhou, 434025, Hubei, China
| | - Ruiqiang Lai
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
| | - Weiwei Chen
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China
| | - Chuanli Lu
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China
| | - Zaid Chachar
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
| | - Siqi Lu
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
| | - Huanzhang Lin
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
| | - Lina Fan
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
| | - Yuanqiang Hu
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
| | - Yuxing An
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China
| | - Xuhui Li
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China.
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China.
| | - Xiangbo Zhang
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China.
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China.
| | - Yongwen Qi
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China.
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China.
- College of Agriculture, Yangtze University, Jingzhou, 434025, Hubei, China.
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China.
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Shen Q, Zhang S, Ge C, Liu S, Chen J, Liu R, Ma H, Song M, Pang C. Genome-wide association study identifies GhSAL1 affects cold tolerance at the seedling emergence stage in upland cotton (Gossypium hirsutum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:27. [PMID: 36810826 DOI: 10.1007/s00122-023-04317-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 02/03/2023] [Indexed: 06/18/2023]
Abstract
Genomic analysis of upland cotton revealed that cold tolerance was associated with ecological distribution. GhSAL1 on chromosome D09 negatively regulated cold tolerance of upland cotton. Cotton can undergo low-temperature stress at the seedling emergence stage, which adversely affects growth and yield; however, the regulatory mechanism underlying cold tolerance remains nebulous. Here, we analyze the phenotypic and physiological parameters in 200 accessions from 5 ecological distributions under constant chilling (CC) and diurnal variation of chilling (DVC) stresses at the seedling emergence stage. All accessions were clustered into four groups, of which Group IV, with most germplasms from the northwest inland region (NIR), had better phenotypes than Groups I-III under the two kinds of chilling stresses. A total of 575 significantly associated single-nucleotide polymorphism (SNP) were identified, and 35 stable genetic quantitative trait loci (QTL) were obtained, of which 5 were associated with traits under CC and DVC stress, respectively, while the remaining 25 were co-associated. The accumulation of dry weight (DW) of seedling was associated with the flavonoid biosynthesis process regulated by Gh_A10G0500. The emergence rate (ER), DW, and total length of seedling (TL) under CC stress were associated with the SNPs variation of Gh_D09G0189 (GhSAL1). GhSAL1HapB was the elite haplotype, which increased ER, DW, and TL by 19.04%, 11.26%, and 7.69%, respectively, compared with that of GhSAL1HapA. The results of virus-induced gene silencing (VIGS) experiment and determination of metabolic substrate content preliminarily illustrated that GhSAL1 negatively regulated cotton cold tolerance through IP3-Ca2+ signaling pathway. The elite haplotypes and candidate genes identified in this study could be used to improve cold tolerance at the seedling emergence stage in future upland cotton breeding.
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Affiliation(s)
- Qian Shen
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
- MOA Key Laboratory of Crop Eco-physiology and Farming system in the Middle Reaches of Yangtze River, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, 430000, Hubei, China
| | - Siping Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Changwei Ge
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Shaodong Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jing Chen
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Ruihua Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Huijuan Ma
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Meizhen Song
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
- Zhengzhou Research Station, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, Henan, China.
| | - Chaoyou Pang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
- Zhengzhou Research Station, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, Henan, China.
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Li C, Dong C, Zhao H, Wang J, Du L, Ai N. Identification of superior parents with high fiber quality using molecular markers and phenotypes based on a core collection of upland cotton ( Gossypium hirsutum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:30. [PMID: 37312963 PMCID: PMC10248707 DOI: 10.1007/s11032-022-01300-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 05/22/2022] [Indexed: 06/15/2023]
Abstract
The combination of molecular markers and phenotypes to select superior parents has become the goal of modern breeders. In this study, 491 upland cotton (Gossypium hirsutum L.) accessions were genotyped using the CottonSNP80K array and then a core collection (CC) was constructed. Superior parents with high fiber quality were identified using molecular markers and phenotypes based on the CC. The Nei diversity index, Shannon's diversity index, and polymorphism information content among chromosomes for 491 accessions ranged from 0.307 to 0.402, 0.467 to 0.587, and 0.246 to 0.316, with mean values of 0.365, 0.542, and 0.291, respectively. A CC containing 122 accessions was established and was categorized into eight clusters based on the K2P genetic distances. From the CC, 36 superior parents (including duplicates) were selected, which contained the elite alleles of markers and ranked in the top 10% of phenotypic values for each fiber quality trait. Among the 36 materials, eight were for fiber length, four were for fiber strength, nine were for fiber micronaire, five were for fiber uniformity, and ten were for fiber elongation. In particular, the nine materials, 348 (Xinluzhong34), 319 (Xinluzhong3), 325 (Xinluzhong9), 397 (L1-14), 205 (XianIII9704), 258 (9D208), 464 (DP201), 467 (DP150), and 465 (DP208), possessed the elite alleles of markers for at least two traits and could be given priority in breeding applications for a more synchronous improvement of fiber quality. The work provides an efficient method for superior parent selection and will facilitate the application of molecular design breeding to cotton fiber quality. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01300-0.
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Affiliation(s)
- Chengqi Li
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Chengguang Dong
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000 China
| | - Haihong Zhao
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Juan Wang
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000 China
| | - Lei Du
- Life Science College, Yuncheng University, Yuncheng, 044000 China
| | - Nijiang Ai
- Shihezi Agricultural Science Research Institute, Shihezi, 832000 China
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Si Z, Jin S, Chen J, Wang S, Fang L, Zhu X, Zhang T, Hu Y. Construction of a high-density genetic map and identification of QTLs related to agronomic and physiological traits in an interspecific (Gossypium hirsutum × Gossypium barbadense) F2 population. BMC Genomics 2022; 23:307. [PMID: 35428176 PMCID: PMC9013169 DOI: 10.1186/s12864-022-08528-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 03/21/2022] [Indexed: 02/06/2023] Open
Abstract
Abstract
Background
Advances in genome sequencing technology, particularly restriction-site associated DNA sequence (RAD-seq) and whole-genome resequencing, have greatly aided the construction of cotton interspecific genetic maps based on single nucleotide polymorphism (SNPs), Indels, and other types of markers. High-density genetic maps can improve accuracy of quantitative trait locus (QTL) mapping, narrow down location intervals, and facilitate identification of the candidate genes.
Result
In this study, 249 individuals from an interspecific F2 population (TM-1 and Hai7124) were re-sequenced, yielding 6303 high-confidence bin markers spanning 5057.13 cM across 26 cotton chromosomes. A total of 3380 recombination hot regions RHRs were identified which unevenly distributed on the 26 chromosomes. Based on this map, 112 QTLs relating to agronomic and physiological traits from seedling to boll opening stage were identified, including 15 loci associated with 14 traits that contained genes harboring nonsynonymous SNPs. We analyzed the sequence and expression of these ten candidate genes and discovered that GhRHD3 (GH_D10G0500) may affect fiber yield while GhGPAT6 (GH_D04G1426) may affect photosynthesis efficiency.
Conclusion
Our research illustrates the efficiency of constructing a genetic map using binmap and QTL mapping on the basis of a certain size of the early-generation population. High-density genetic map features high recombination exchanges in number and distribution. The QTLs and the candidate genes identified based on this high-density genetic map may provide important gene resources for the genetic improvement of cotton.
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Liu X, Yang L, Wang J, Wang Y, Guo Z, Li Q, Yang J, Wu Y, Chen L, Teng Z, Liu D, Liu D, Guo K, Zhang Z. Analyzing Quantitative Trait Loci for Fiber Quality and Yield-Related Traits From a Recombinant Inbred Line Population With Gossypium hirsutum Race palmeri as One Parent. FRONTIERS IN PLANT SCIENCE 2022; 12:817748. [PMID: 35046989 PMCID: PMC8763314 DOI: 10.3389/fpls.2021.817748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 12/01/2021] [Indexed: 06/14/2023]
Abstract
Fiber quality and yield-related traits are important agronomic traits in cotton breeding. To detect the genetic basis of fiber quality and yield related traits, a recombinant inbred line (RIL) population consisting of 182 lines was established from a cross between Gossypium hirsutum cultivar CCRI35 and G. hirsutum race palmeri accession TX-832. The RIL population was deeply genotyped using SLAF-seq and was phenotyped in six environments. A high-density genetic linkage map with 15,765 SNP markers and 153 SSR markers was constructed, with an average distance of 0.30 cM between adjacent markers. A total of 210 fiber quality quantitative trait loci (QTLs) and 73 yield-related QTLs were identified. Of the detected QTLs, 62 fiber quality QTLs and 10 yield-related QTLs were stable across multiple environments. Twelve and twenty QTL clusters were detected on the At and Dt subgenome, respectively. Twenty-three major QTL clusters were further validated through associated analysis and five candidate genes of four stable fiber quality QTLs were identified. This study revealed elite loci influencing fiber quality and yield and significant phenotypic selection regions during G. hirsutum domestication, and set a stage for future utilization of molecular marker assisted breeding in cotton breeding programs.
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Kumar P, Nimbal S, Sangwan RS, Budhlakoti N, Singh V, Mishra DC, Sagar, Choudhary RR. Identification of Novel Marker-Trait Associations for Lint Yield Contributing Traits in Upland Cotton ( Gossypium hirsutum L.) Using SSRs. FRONTIERS IN PLANT SCIENCE 2021; 12:653270. [PMID: 34122477 PMCID: PMC8187916 DOI: 10.3389/fpls.2021.653270] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 04/16/2021] [Indexed: 11/10/2023]
Abstract
Improving the yield of lint is the main objective for most of the cotton crop improvement programs throughout the world as it meets the demand of fiber for textile industries. In the current study, 96 genotypes of Gossypium hirsutum were used to find novel simple sequence repeat marker-based associations for lint yield contributing traits by linkage disequilibrium. Extensive phenotyping of 96 genotypes for various agronomic traits was done for two consecutive years (2018 and 2019) in early, normal, and late sown environments. Out of 168 SSR markers screened over the 96 genotypes, a total of 97 polymorphic markers containing 293 alleles were used for analysis. Three different models, i.e., mixed linear model (MLM), compressed mixed linear model (CMLM), and multiple locus mixed linear model (MLMM), were used to detect the significant marker-trait associations for six different environments separately. A total of 38 significant marker-trait associations that were common to at least two environments were considered as promising associations and detailed annotation of the significant markers has been carried out. Twenty-two marker-trait associations were found to be novel in the current study. These results will be very useful for crop improvement programs using marker-assisted cotton breeding.
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Affiliation(s)
- Pawan Kumar
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Somveer Nimbal
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Rajvir Singh Sangwan
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Neeraj Budhlakoti
- Indian Council of Agricultural Research-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Varsha Singh
- Department of Molecular Biology and Biotechnology, CCS Haryana Agricultural University, Hisar, India
| | - Dwijesh Chandra Mishra
- Indian Council of Agricultural Research-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Sagar
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Raju Ram Choudhary
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
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Selvaraj R, Singh AK, Singh VK, Abbai R, Habde SV, Singh UM, Kumar A. Superior haplotypes towards development of low glycemic index rice with preferred grain and cooking quality. Sci Rep 2021; 11:10082. [PMID: 33980871 PMCID: PMC8115083 DOI: 10.1038/s41598-021-87964-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 03/19/2021] [Indexed: 02/03/2023] Open
Abstract
Increasing trends in the occurrence of diabetes underline the need to develop low glycemic index (GI) rice with preferred grain quality. In the current study, a diverse set of 3 K sub-panel of rice consisting of 150 accessions was evaluated for resistant starch and predicted glycemic index, including nine other quality traits under transplanted situation. Significant variations were noticed among the accessions for the traits evaluated. Trait associations had shown that amylose content possess significant positive and negative association with resistant starch and predicted glycemic index. Genome-wide association studies with 500 K SNPs based on MLM model resulted in a total of 41 marker-trait associations (MTAs), which were further confirmed and validated with mrMLM multi-locus model. We have also determined the allelic effect of identified MTAs for 11 targeted traits and found favorable SNPs for 8 traits. A total of 11 genes were selected for haplo-pheno analysis to identify the superior haplotypes for the target traits where haplotypes ranges from 2 (Os10g0469000-GC) to 15 (Os06g18720-AC). Superior haplotypes for RS and PGI, the candidate gene Os06g11100 (H4-3.28% for high RS) and Os08g12590 (H13-62.52 as intermediate PGI). The identified superior donors possessing superior haplotype combinations may be utilized in Haplotype-based breeding to developing next-generation tailor-made high quality healthier rice varieties suiting consumer preference and market demand.
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Affiliation(s)
- Ramchander Selvaraj
- IRRI South Asia Hub (IRRI-SAH), ICRISAT Campus, Patancheru, Hyderabad, India
| | - Arun Kumar Singh
- IRRI South Asia Hub (IRRI-SAH), ICRISAT Campus, Patancheru, Hyderabad, India
| | - Vikas Kumar Singh
- IRRI South Asia Hub (IRRI-SAH), ICRISAT Campus, Patancheru, Hyderabad, India
| | - Ragavendran Abbai
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Sonali Vijay Habde
- South-Asia Regional Centre (SARC), International Rice Research Institute (IRRI), Varanasi, India
| | - Uma Maheshwar Singh
- South-Asia Regional Centre (SARC), International Rice Research Institute (IRRI), Varanasi, India
| | - Arvind Kumar
- IRRI South Asia Hub (IRRI-SAH), ICRISAT Campus, Patancheru, Hyderabad, India.
- South-Asia Regional Centre (SARC), International Rice Research Institute (IRRI), Varanasi, India.
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8
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Geng X, Sun G, Qu Y, Sarfraz Z, Jia Y, He S, Pan Z, Sun J, Iqbal MS, Wang Q, Qin H, Liu J, Liu H, Yang J, Ma Z, Xu D, Yang J, Zhang J, Li Z, Cai Z, Zhang X, Zhang X, Zhou G, Li L, Zhu H, Wang L, Pang B, Du X. Genome-wide dissection of hybridization for fiber quality- and yield-related traits in upland cotton. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 104:1285-1300. [PMID: 32996179 PMCID: PMC7756405 DOI: 10.1111/tpj.14999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 07/14/2020] [Accepted: 09/03/2020] [Indexed: 06/11/2023]
Abstract
An evaluation of combining ability can facilitate the selection of suitable parents and superior F1 hybrids for hybrid cotton breeding, although the molecular genetic basis of combining ability has not been fully characterized. In the present study, 282 female parents were crossed with four male parents in accordance with the North Carolina II mating scheme to generate 1128 hybrids. The parental lines were genotyped based on restriction site-associated DNA sequencing and 306 814 filtered single nucleotide polymorphisms were used for genome-wide association analysis involving the phenotypes, general combining ability (GCA) values, and specific combining ability values of eight fiber quality- and yield-related traits. The main results were: (i) all parents could be clustered into five subgroups based on population structure analyses and the GCA performance of the female parents had significant differences between subgroups; (ii) 20 accessions with a top 5% GCA value for more than one trait were identified as elite parents for hybrid cotton breeding; (iii) 120 significant single nucleotide polymorphisms, clustered into 66 quantitative trait loci, such as the previously reported Gh_A07G1769 and GhHOX3 genes, were found to be significantly associated with GCA; and (iv) identified quantitative trait loci for GCA had a cumulative effect on GCA of the accessions. Overall, our results suggest that pyramiding the favorable loci for GCA may improve the efficiency of hybrid cotton breeding.
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Affiliation(s)
- Xiaoli Geng
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Gaofei Sun
- Anyang Institute of TechnologyAnyang455000China
| | - Yujie Qu
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Zareen Sarfraz
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Yinhua Jia
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Shoupu He
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Zhaoe Pan
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Junling Sun
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Muhammad S. Iqbal
- Cotton Research StationAyub Agricultural Research InstituteFaisalabad38000Pakistan
| | - Qinglian Wang
- Henan Institute of Science and TechnologyXinxiang453003China
| | - Hongde Qin
- Cash Crop InstituteHubei Academy of Agricultural SciencesWuhan430000China
| | - Jinhai Liu
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Hui Liu
- Jing Hua Seed Industry Technologies IncJingzhou434000China
| | - Jun Yang
- Cotton Research Institute of Jiangxi ProvinceJiujiang332000China
| | - Zhiying Ma
- Key Laboratory of Crop Germplasm Resources of HebeiHebei Agricultural UniversityBaoding071000China
| | - Dongyong Xu
- Guoxin Rural Technical Service AssociationHejian062450China
| | - Jinlong Yang
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | | | - Zhikun Li
- Key Laboratory of Crop Germplasm Resources of HebeiHebei Agricultural UniversityBaoding071000China
| | - Zhongmin Cai
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Xuelin Zhang
- Hunan Cotton Research InstituteChangde415000China
| | - Xin Zhang
- Henan Institute of Science and TechnologyXinxiang453003China
| | - Guanyin Zhou
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Lin Li
- Zhongli Company of ShandongDongying257000China
| | - Haiyong Zhu
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Liru Wang
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Baoyin Pang
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Xiongming Du
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
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9
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Novel Vegetation Indices for Cotton Boll Opening Status Estimation Using Sentinel-2 Data. REMOTE SENSING 2020. [DOI: 10.3390/rs12111712] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
The application of chemical harvest aids to defoliate leaves and ripen bolls plays a significant role in the once-over machine harvest of cotton (Gossypium hirsutum L.) fields. The boll opening rate (BOR) is a key indicator for the determination of harvest aid spraying times. However, the most commonly used method to determine BOR is manual investigation, which is subjective and cannot have a holistic judgment of the entire area. Remote sensing can be employed to overcome these limitations, due to a wide field of vision, acceptably spatial and temporal resolution, and rich spectral information beyond the perception of the human eye. The reflectance of open cotton bolls is relatively high in the visible and near-infrared bands. High reflectance of open bolls has a great influence on the reflectance of the mixed pixels on remote sensing imagery. Therefore, it is an effective method to detect boll opening status by constructing vegetation indices with the sensitive spectral bands of imagery. In this study, we proposed two new vegetation indices based on Sentinel-2 remote sensing data, namely, the boll area ratio index (BARI) and the boll opening rate index (BORI), in order to estimate the boll opening status on a regional scale. The proposed indices were strongly correlated with the boll area ratio (BAR) and BOR. In particular, BARI exhibited the most accurate and robust performance with BAR in the prediction (R2 = 0.754, RMSE = 2.56%) and validation (R2 = 0.706, RMSE = 5.00%) among all the indices, including published indices we chose. Furthermore, when comparing to all other indices, BORI demonstrated the best and satisfactory estimation with BOR in the prediction (R2 = 0.675, RMSE = 7.96%) and validation (R2 = 0.616, RMSE = 2.79%). Meanwhile, an exponential growth relationship between BOR and BAR was identified, and the underlying mechanisms behind this phenomenon were discussed. Overall, through our study, we provided convenient and accurate vegetation indices for the investigation of boll opening status in a cotton-producing area by accessible and free Sentinel-2 imagery.
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Mwando E, Han Y, Angessa TT, Zhou G, Hill CB, Zhang XQ, Li C. Genome-Wide Association Study of Salinity Tolerance During Germination in Barley ( Hordeum vulgare L.). FRONTIERS IN PLANT SCIENCE 2020; 11:118. [PMID: 32153619 PMCID: PMC7047234 DOI: 10.3389/fpls.2020.00118] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 01/27/2020] [Indexed: 05/21/2023]
Abstract
Barley seeds need to be able to germinate and establish seedlings in saline soils in Mediterranean-type climates. Despite being a major cereal crop, barley has few reported quantitative trait loci (QTL) and candidate genes underlying salt tolerance at the germination stage. Breeding programs targeting salinity tolerance at germination require an understanding of genetic loci and alleles in the current germplasm. In this study, we investigated seed-germination-related traits under control and salt stress conditions in 350 diverse barley accessions. A genome-wide association study, using ~24,000 genetic markers, was undertaken to detect marker-trait associations (MTA) and the underlying candidate genes for salinity tolerance during germination. We detected 19 loci containing 52 significant salt-tolerance-associated markers across all chromosomes, and 4 genes belonging to 4 family functions underlying the predicted MTAs. Our results provide new genetic resources and information to improve salt tolerance at germination in future barley varieties via genomic and marker-assisted selection and to open up avenues for further functional characterization of the identified candidate genes.
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Affiliation(s)
- Edward Mwando
- Western Barley Genetics Alliance, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA, Australia
- Western Australian State Agricultural Biotechnology Centre, Murdoch University, Perth, WA, Australia
| | - Yong Han
- Western Barley Genetics Alliance, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA, Australia
- Western Australian State Agricultural Biotechnology Centre, Murdoch University, Perth, WA, Australia
| | - Tefera Tolera Angessa
- Western Barley Genetics Alliance, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA, Australia
- Western Australian State Agricultural Biotechnology Centre, Murdoch University, Perth, WA, Australia
- Department of Primary Industries and Regional Development Government of Western Australia, Perth, WA, Australia
| | - Gaofeng Zhou
- Western Barley Genetics Alliance, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA, Australia
- Department of Primary Industries and Regional Development Government of Western Australia, Perth, WA, Australia
| | - Camilla Beate Hill
- Western Barley Genetics Alliance, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA, Australia
- Western Australian State Agricultural Biotechnology Centre, Murdoch University, Perth, WA, Australia
| | - Xiao-Qi Zhang
- Western Barley Genetics Alliance, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA, Australia
- Western Australian State Agricultural Biotechnology Centre, Murdoch University, Perth, WA, Australia
| | - Chengdao Li
- Western Barley Genetics Alliance, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA, Australia
- Western Australian State Agricultural Biotechnology Centre, Murdoch University, Perth, WA, Australia
- Department of Primary Industries and Regional Development Government of Western Australia, Perth, WA, Australia
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11
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Abdelraheem A, Elassbli H, Zhu Y, Kuraparthy V, Hinze L, Stelly D, Wedegaertner T, Zhang J. A genome-wide association study uncovers consistent quantitative trait loci for resistance to Verticillium wilt and Fusarium wilt race 4 in the US Upland cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:563-577. [PMID: 31768602 DOI: 10.1007/s00122-019-03487-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 11/13/2019] [Indexed: 05/16/2023]
Abstract
A high-resolution GWAS detected consistent QTL for resistance to Verticillium wilt and Fusarium wilt race 4 in 376 U.S. Upland cotton accessions based on six independent replicated greenhouse tests. Verticillium wilt (VW, caused by Verticillium dahliae Kleb.) and Fusarium wilt (FOV, caused by Fusarium oxysporum f.sp. vasinfectum Atk. Sny & Hans) are the most important soil-borne fungal diseases in cotton. To augment and refine resistance quantitative trait loci (QTL), we conducted a genome-wide association study (GWAS) using high-density genotyping with the CottonSNP63K array. Resistance of 376 US Upland cotton accessions to a defoliating VW and virulent FOV4 was evaluated in four and two independent replicated greenhouse tests, respectively. A total of 15 and 13 QTL for VW and FOV4 resistances were anchored by 30 (on five chromosomes) and 56 (on six chromosomes) significant single nucleotide polymorphic (SNPs) markers, respectively. QTL on c8, c10, c16, and c21 were consistent in two or more tests for VW resistance, while two QTL on c8 and c14 were consistent for FOV4 resistance in two tests. Two QTL clusters on c16 and c19 were observed for both VW and FOV4 resistance, suggesting that these genomic regions may harbor genes in response to both diseases. Using BLAST search against the sequenced TM-1 genome, 30 and 35 candidate genes were identified on four QTL for VW resistance and on three QTL for FOV4 resistance, respectively. These genomic regions were rich in NBS-LRR genes presented in clusters. The results create opportunities for further studies to determine the correlations of field resistance with these QTL, molecular examinations of VW and FOV4 resistances, marker-assisted selection (MAS) and eventual cloning of QTL for disease resistance in cotton.
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Affiliation(s)
- Abdelraheem Abdelraheem
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Hanan Elassbli
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Yi Zhu
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Vasu Kuraparthy
- Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, 27695-7620, USA
| | - Lori Hinze
- Crop Germplasm Research, USDA-ARS, College Station, TX, 77845, USA
| | - David Stelly
- Department of Soil and Crop Sciences, Texas A & M University, College Station, TX, 77843, USA
| | | | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
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12
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Wang Y, Li G, Guo X, Sun R, Dong T, Yang Q, Wang Q, Li C. Dissecting the genetic architecture of seed-cotton and lint yields in Upland cotton using genome-wide association mapping. BREEDING SCIENCE 2019; 69:611-620. [PMID: 31988625 PMCID: PMC6977443 DOI: 10.1270/jsbbs.19057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 07/23/2019] [Indexed: 05/18/2023]
Abstract
Seed-cotton yield (SY) and lint yield (LY) are the most important yield traits of cotton. Thus, it is critical to dissect their genetic architecture. Upland cotton (Gossypium hirsutum) is widely grown worldwide. In this study, a genome-wide association mapping was performed based on the CottonSNP80K array to dissect the genetic architecture of SY and LY in Upland cotton. Twenty-three significant associations were detected within four environments, including 11 associated with SY and 12 associated with LY. Seven single nucleotide polymorphisms (SNPs), TM234, TM237, TM247, TM255, TM256, TM263, and TM264, were co-associated with the two traits, which may indicate pleiotropy or intergenic tight linkages. Five SNPs, TM13332, TM39771, TM57119, TM81653, and TM81660, were coincided with those of previous reports and could be used in marker-assisted selection. Combining functional annotations with expression analyses of the genes identified within 400 kb of the significantly associated SNPs, we hypothesize that the three genes, Gh_D05G1077 and Gh_D13G1571 for SY, and Gh_A11G0775 for LY, may have the potential to increase cotton yield. The results would provide useful information for understanding the genetic basis of yield traits in Upland cotton and for facilitating its high-yield breeding through molecular design.
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Affiliation(s)
- Yuanyuan Wang
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Guirong Li
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Xinlei Guo
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics,
Beijing 100081,
China
| | - Runrun Sun
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Tao Dong
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Qiuyue Yang
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Qinglian Wang
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
| | - Chengqi Li
- Collaborative Innovation Center of Modern Biological Breeding, Henan Institute of Science and Technology,
Xinxiang 453003,
China
- Corresponding author (e-mail: )
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13
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Feng GL, Zhai FY, Liu HL, Ai NJ. Identification of genomewide single-nucleotide polymorphisms associated with presummer, summer and autumn bolls in upland cotton. J Genet 2019; 98:72. [PMID: 31544781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Presummer, summer, and autumn bolls (PSB, SB and AB, respectively) in cotton are related to both maturity and yield. Therefore, studying their genetic basis is important for breeding purposes. In this study, we developed an association analysis panel consisting of 169 upland cotton accessions. The panel was phenotyped for PSB, SB and AB across four environments and genotyped using a Cotton SNP80K array. Single-nucleotide polymorphisms (SNPs) associated with these three traits were identified by a genomewide association study. A total of 53,848 high-quality SNPs were screened, and 91 significant trait-associated SNPs were detected. Of the 91 SNPs 33 were associated with PSB, 21 with SB and 37 with AB. Three SNPs for PSB (TM10410, TM13158 and TM21762) and five for AB (TM13730, TM13733, TM13834, TM29666 and TM43214) were repeatedly detected in two environments or by two methods. These eight SNPs exhibited high phenotypic variation of more than 10%, thus allowing their use formarker-assisted selection. The candidate genes for target traits were also identified. These findings provide a theoretical basis for the improvement of early maturity and yield in cotton breeding programmes.
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Affiliation(s)
- Guo-Li Feng
- Shihezi Agricultural Science Research Institute, Shihezi 832000, Xinjiang Province, People's Republic of China.
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14
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Evaluation of genomic selection methods for predicting fiber quality traits in Upland cotton. Mol Genet Genomics 2019; 295:67-79. [DOI: 10.1007/s00438-019-01599-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 07/29/2019] [Indexed: 01/25/2023]
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15
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Identification of genomewide single-nucleotide polymorphisms associated with presummer, summer and autumn bolls in upland cotton. J Genet 2019. [DOI: 10.1007/s12041-019-1118-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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16
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Shi Y, Liu A, Li J, Zhang J, Zhang B, Ge Q, Jamshed M, Lu Q, Li S, Xiang X, Gong J, Gong W, Shang H, Deng X, Pan J, Yuan Y. Dissecting the genetic basis of fiber quality and yield traits in interspecific backcross populations of Gossypium hirsutum × Gossypium barbadense. Mol Genet Genomics 2019; 294:1385-1402. [PMID: 31201519 DOI: 10.1007/s00438-019-01582-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2018] [Accepted: 05/29/2019] [Indexed: 12/31/2022]
Abstract
Fiber quality and yield are important traits of cotton. Quantitative trait locus (QTL) mapping is a prerequisite for marker-assisted selection (MAS) in cotton breeding. To identify QTLs for fiber quality and yield traits, 4 backcross-generation populations (BC1F1, BC1S1, BC2F1, and BC3F0) were developed from an interspecific cross between CCRI36 (Gossypium hirsutum L.) and Hai1 (G. barbadense L.). A total of 153 QTLs for fiber quality and yield traits were identified based on data from the BC1F1, BC1S1, BC2F1 and BC3F0 populations in the field and from the BC2F1 population in an artificial disease nursery using a high-density genetic linkage map with 2292 marker loci covering 5115.16 centimorgans (cM) from the BC1F1 population. These QTLs were located on 24 chromosomes, and each could explain 4.98-19.80% of the observed phenotypic variations. Among the 153 QTLs, 30 were consistent with those identified previously. Specifically, 23 QTLs were stably detected in 2 or 3 environments or generations, 6 of which were consistent with those identified previously and the other 17 of which were stable and novel. Ten QTL clusters for different traits were found and 9 of them were novel, which explained the significant correlations among some phenotypic traits in the populations. The results including these stable or consensus QTLs provide valuable information for marker-assisted selection (MAS) in cotton breeding and will help better understand the genetic basis of fiber quality and yield traits, which can then be used in QTL cloning.
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Affiliation(s)
- Yuzhen Shi
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Baocai Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Muhammad Jamshed
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Quanwei Lu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Shaoqi Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xianghui Xiang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
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Jaiswal V, Gupta S, Gahlaut V, Muthamilarasan M, Bandyopadhyay T, Ramchiary N, Prasad M. Genome-Wide Association Study of Major Agronomic Traits in Foxtail Millet (Setaria italica L.) Using ddRAD Sequencing. Sci Rep 2019; 9:5020. [PMID: 30903013 PMCID: PMC6430830 DOI: 10.1038/s41598-019-41602-6] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 03/05/2019] [Indexed: 12/17/2022] Open
Abstract
Foxtail millet (Setaria italica), the second largest cultivated millet crop after pearl millet, is utilized for food and forage globally. Further, it is also considered as a model crop for studying agronomic, nutritional and biofuel traits. In the present study, a genome-wide association study (GWAS) was performed for ten important agronomic traits in 142 foxtail millet core eco-geographically diverse genotypes using 10 K SNPs developed through GBS-ddRAD approach. Number of SNPs on individual chromosome ranged from 844 (chromosome 5) to 2153 (chromosome 8) with an average SNP frequency of 25.9 per Mb. The pairwise linkage disequilibrium (LD) estimated using the squared-allele frequency correlations was found to decay rapidly with the genetic distance of 177 Kb. However, for individual chromosome, LD decay distance ranged from 76 Kb (chromosome 6) to 357 Kb (chromosome 4). GWAS identified 81 MTAs (marker-trait associations) for ten traits across the genome. High confidence MTAs for three important agronomic traits including FLW (flag leaf width), GY (grain yield) and TGW (thousand-grain weight) were identified. Significant pyramiding effect of identified MTAs further supplemented its importance in breeding programs. Desirable alleles and superior genotypes identified in the present study may prove valuable for foxtail millet improvement through marker-assisted selection.
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Affiliation(s)
- Vandana Jaiswal
- School of Life Science, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Sarika Gupta
- School of Life Science, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Vijay Gahlaut
- Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, 110021, India
| | - Mehanathan Muthamilarasan
- National Institute of Plant Genome Research, New Delhi, 110067, India
- ICAR-National Research Centre on Plant Biotechnology, LBS Centre, Pusa Campus, New Delhi, 110012, India
| | | | - Nirala Ramchiary
- School of Life Science, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Manoj Prasad
- National Institute of Plant Genome Research, New Delhi, 110067, India.
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Ma L, Wang Y, Ijaz B, Hua J. Cumulative and different genetic effects contributed to yield heterosis using maternal and paternal backcross populations in Upland cotton. Sci Rep 2019; 9:3984. [PMID: 30850683 PMCID: PMC6408543 DOI: 10.1038/s41598-019-40611-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 02/20/2019] [Indexed: 11/15/2022] Open
Abstract
Heterosis has been utilized in commercial production, but the heterosis mechanism has remained vague. Hybrid cotton is suitable to dissect the heterosis mechanism. In order to explore the genetic basis of heterosis in Upland cotton, we generated paternal and maternal backcross (BC/P and BC/M) populations. Data for yield and yield-component traits were collected over 2 years in three replicated BC/P field trials and four replicated BC/M field trials. At single-locus level, 26 and 27 QTLs were identified in BC/P and BC/M populations, respectively. Six QTLs shared in both BC populations. A total of 27 heterotic loci were detected. Partial dominant and over-dominant QTLs mainly determined yield heterosis in the BC/P and BC/M populations. QTLs for different traits displayed varied genetic effects in two BC populations. Eleven heterotic loci overlapped with QTLs but no common heterotic locus was detected in both BC populations. We resolved the 333 kb (48 genes) and 516 kb (25 genes) physical intervals based on 16 QTL clusters and 35 common QTLs, respectively, in more than one environment or population. We also identified 189 epistatic QTLs and a number of QTL × environment interactions in two BC populations and the corresponding MPH datasets. The results indicated that cumulative effects contributed to yield heterosis in Upland cotton, including epistasis, QTL × environment interaction, additive, partial dominance and over-dominance.
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Affiliation(s)
- Lingling Ma
- Laboratory of Cotton Genetics, Genomics and Breeding/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Yumei Wang
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, 430064, Hubei, China
| | - Babar Ijaz
- Laboratory of Cotton Genetics, Genomics and Breeding/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Jinping Hua
- Laboratory of Cotton Genetics, Genomics and Breeding/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
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19
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Ijaz B, Zhao N, Kong J, Hua J. Fiber Quality Improvement in Upland Cotton ( Gossypium hirsutum L.): Quantitative Trait Loci Mapping and Marker Assisted Selection Application. FRONTIERS IN PLANT SCIENCE 2019; 10:1585. [PMID: 31921240 PMCID: PMC6917639 DOI: 10.3389/fpls.2019.01585] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 11/12/2019] [Indexed: 05/17/2023]
Abstract
Genetic improvement in fiber quality is one of the main challenges for cotton breeders. Fiber quality traits are controlled by multiple genes and are classified as complex quantitative traits, with a negative relationship with yield potential, so the genetic gain is low in traditional genetic improvement by phenotypic selection. The availability of Gossypium genomic sequences facilitates the development of high-throughput molecular markers, quantitative trait loci (QTL) fine mapping and gene identification, which helps us to validate candidate genes and to use marker assisted selection (MAS) on fiber quality in breeding programs. Based on developments of high density linkage maps, QTLs fine mapping, marker selection and omics, we have performed trait dissection on fiber quality traits in diverse populations of upland cotton. QTL mapping combined with multi-omics approaches such as, RNA sequencing datasets to identify differentially expressed genes have benefited the improvement of fiber quality. In this review, we discuss the application of molecular markers, QTL mapping and MAS for fiber quality improvement in upland cotton.
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Affiliation(s)
- Babar Ijaz
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Nan Zhao
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Jie Kong
- Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Jinping Hua
- Laboratory of Cotton Genetics, Genomics and Breeding/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
- *Correspondence: Jinping Hua,
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20
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Liu R, Gong J, Xiao X, Zhang Z, Li J, Liu A, Lu Q, Shang H, Shi Y, Ge Q, Iqbal MS, Deng X, Li S, Pan J, Duan L, Zhang Q, Jiang X, Zou X, Hafeez A, Chen Q, Geng H, Gong W, Yuan Y. GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers. FRONTIERS IN PLANT SCIENCE 2018; 9:1067. [PMID: 30283462 PMCID: PMC6157485 DOI: 10.3389/fpls.2018.01067] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Accepted: 07/02/2018] [Indexed: 05/18/2023]
Abstract
It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18-24.45 and 1.68-28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly "pleiotropic." This study provided important information for MAS and candidate gene functional studies.
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Affiliation(s)
- Ruixian Liu
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Juwu Gong
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xianghui Xiao
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Zhen Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanwei Lu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Muhammad S. Iqbal
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shaoqi Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Li Duan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Qi Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiao Jiang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xianyan Zou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Abdul Hafeez
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Quanjia Chen
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
| | - Hongwei Geng
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Youlu Yuan
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
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Su J, Ma Q, Li M, Hao F, Wang C. Multi-Locus Genome-Wide Association Studies of Fiber-Quality Related Traits in Chinese Early-Maturity Upland Cotton. FRONTIERS IN PLANT SCIENCE 2018; 9:1169. [PMID: 30166989 PMCID: PMC6107031 DOI: 10.3389/fpls.2018.01169] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 07/23/2018] [Indexed: 05/04/2023]
Abstract
Early-maturity varieties of upland cotton are becoming increasingly important for farmers to improve their economic benefits through double cropping practices and mechanical harvesting production in China. However, fiber qualities of early-maturing varieties are relatively poor compared with those of middle- and late- maturing ones. Therefore, it is crucial for researchers to elucidate the genetic bases controlling fiber-quality related traits in early-maturity cultivars, and to improve synergistically cotton earliness and fiber quality. Here, multi-locus genome-wide association studies (ML-GWAS) were conducted in a panel consisting of 160 early-maturing cotton accessions. Each accession was genotyped by 72,792 high-quality single nucleotide polymorphisms (SNPs) using specific-locus amplified fragment sequencing (SLAF-seq) approach, and fiber quality-related traits under four environmental conditions were measured. Applying at least three ML-GWAS methods, a total of 70 significant quantitative trait nucleotides (QTNs) were identified to be associated with five objective traits, including fiber length (FL), fiber strength (FS), fiber micronaire (FM), fiber uniformity (FU) and fiber elongation (FE). Among these QTNs, D11_21619830, A05_28352019 and D03_34920546 were found to be significantly associated with FL, FS, and FM, respectively, across at least two environments. Among 96 genes located in the three target genomic regions (A05: 27.95 28.75, D03: 34.52 35.32, and D11: 21.22 22.02 Mbp), six genes (Gh_A05G2325, Gh_A05G2329, Gh_A05G2334, Gh_D11G1853, Gh_D11G1876, and Gh_D11G1879) were detected to be highly expressed in fibers relative to other eight tissues by transcriptome sequencing method in 12 cotton tissues. Together, multiple favorable QTN alleles and six candidate key genes were characterized to regulate fiber development in early-maturity cotton. This will lay a solid foundation for breeding novel cotton varieties with earliness and excellent fiber-quality in the future.
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Affiliation(s)
- Junji Su
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
| | - Qi Ma
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
| | - Mei Li
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Fushun Hao
- State Key Laboratory of Cotton Biology, Henan Key Laboratory of Plant Stress Biology, College of Life Science, Henan University, Kaifeng, China
| | - Caixiang Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
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Dong C, Wang J, Yu Y, Ju L, Zhou X, Ma X, Mei G, Han Z, Si Z, Li B, Chen H, Zhang T. Identifying Functional Genes Influencing Gossypium hirsutum Fiber Quality. FRONTIERS IN PLANT SCIENCE 2018; 9:1968. [PMID: 30687363 PMCID: PMC6334163 DOI: 10.3389/fpls.2018.01968] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 12/18/2018] [Indexed: 05/21/2023]
Abstract
Fiber quality is an important economic index and a major breeding goal in cotton, but direct phenotypic selection is often hindered due to environmental influences and linkage with yield traits. A genome-wide association study (GWAS) is a powerful tool to identify genes associated with phenotypic traits. In this study, we identified fiber quality genes in upland cotton (Gossypium hirsutum L.) using GWAS based on a high-density CottonSNP80K array and multiple environment tests. A total of 30 and 23 significant single nucleotide polymorphisms (SNPs) associated with five fiber quality traits were identified across the 408 cotton accessions in six environments and the best linear unbiased predictions, respectively. Among these SNPs, seven loci were the same, and 128 candidate genes were predicted in a 1-Mb region (±500 kb of the peak SNP). Furthermore, two major genome regions (GR1 and GR2) associated with multiple fiber qualities in multiple environments on chromosomes A07 and A13 were identified, and within them, 22 candidate genes were annotated. Of these, 11 genes were expressed [log2(1 + FPKM)>1] in the fiber development stages (5, 10, 20, and 25 dpa) using RNA-Seq. This study provides fundamental insight relevant to identification of genes associated with fiber quality and will accelerate future efforts toward improving fiber quality of upland cotton.
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Affiliation(s)
- Chengguang Dong
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
| | - Juan Wang
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
| | - Yu Yu
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
| | - Longzhen Ju
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Xiaofeng Zhou
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
| | - Xiaomei Ma
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
| | - Gaofu Mei
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Zegang Han
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Zhanfeng Si
- Department of Agronomy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Baocheng Li
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
| | - Hong Chen
- Key Laboratory of China Northwestern Inland Region, Ministry of Agriculture, Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, China
- *Correspondence: Hong Chen, Tianzhen Zhang,
| | - Tianzhen Zhang
- Department of Agronomy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
- *Correspondence: Hong Chen, Tianzhen Zhang,
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Li C, Fu Y, Sun R, Wang Y, Wang Q. Single-Locus and Multi-Locus Genome-Wide Association Studies in the Genetic Dissection of Fiber Quality Traits in Upland Cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2018; 9:1083. [PMID: 30177935 PMCID: PMC6109694 DOI: 10.3389/fpls.2018.01083] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 07/04/2018] [Indexed: 05/04/2023]
Abstract
A major breeding target in Upland cotton (Gossypium hirsutum L.) is to improve the fiber quality. To address this issue, 169 diverse accessions, genotyped by 53,848 high-quality single-nucleotide polymorphisms (SNPs) and phenotyped in four environments, were used to conduct genome-wide association studies (GWASs) for fiber quality traits using three single-locus and three multi-locus models. As a result, 342 quantitative trait nucleotides (QTNs) controlling fiber quality traits were detected. Of the 342 QTNs, 84 were simultaneously detected in at least two environments or by at least two models, which include 29 for fiber length, 22 for fiber strength, 11 for fiber micronaire, 12 for fiber uniformity, and 10 for fiber elongation. Meanwhile, nine QTNs with 10% greater sizes (R2) were simultaneously detected in at least two environments and between single- and multi-locus models, which include TM80185 (D13) for fiber length, TM1386 (A1) and TM14462 (A6) for fiber strength, TM18616 (A7), TM54735 (D3), and TM79518 (D12) for fiber micronaire, TM77489 (D12) and TM81448 (D13) for fiber uniformity, and TM47772 (D1) for fiber elongation. This indicates the possibility of marker-assisted selection in future breeding programs. Among 455 genes within the linkage disequilibrium regions of the nine QTNs, 113 are potential candidate genes and four are promising candidate genes. These findings reveal the genetic control underlying fiber quality traits and provide insights into possible genetic improvements in Upland cotton fiber quality.
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Affiliation(s)
- Chengqi Li
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Yuanzhi Fu
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Runrun Sun
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Yuanyuan Wang
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
| | - Qinglian Wang
- Collaborative Innovation Center of Modern Biological Breeding, School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China
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Li T, Ma X, Li N, Zhou L, Liu Z, Han H, Gui Y, Bao Y, Chen J, Dai X. Genome-wide association study discovered candidate genes of Verticillium wilt resistance in upland cotton (Gossypium hirsutum L.). PLANT BIOTECHNOLOGY JOURNAL 2017; 15:1520-1532. [PMID: 28371164 PMCID: PMC5698051 DOI: 10.1111/pbi.12734] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 03/16/2017] [Accepted: 03/21/2017] [Indexed: 05/03/2023]
Abstract
Verticillium wilt (VW), caused by infection by Verticillium dahliae, is considered one of the most yield-limiting diseases in cotton. To examine the genetic architecture of cotton VW resistance, we performed a genome-wide association study (GWAS) using a panel of 299 accessions and 85 630 single nucleotide polymorphisms (SNPs) detected using the specific-locus amplified fragment sequencing (SLAF-seq) approach. Trait-SNP association analysis detected a total of 17 significant SNPs at P < 1.17 × 10-5 (P = 1/85 630, -log10 P = 4.93); the peaks of SNPs associated with VW resistance on A10 were continuous and common in three environments (RDIG2015, RDIF2015 and RDIF2016). Haplotype block structure analysis predicted 22 candidate genes for VW resistance based on A10_99672586 with a minimum P-value (-log10 P = 6.21). One of these genes (CG02) was near the significant SNP A10_99672586 (0.26 Mb), located in a 372-kb haplotype block, and its Arabidopsis AT3G25510 homologues contain TIR-NBS-LRR domains that may be involved in disease resistance response. Real-time quantitative PCR and virus-induced gene silencing (VIGS) analysis showed that CG02 was specific to up-regulation in the resistant (R) genotype Zhongzhimian2 (ZZM2) and that silenced plants were more susceptible to V. dahliae. These results indicate that CG02 is likely the candidate gene for resistance against V. dahliae in cotton. The identified locus or gene may serve as a promising target for genetic engineering and selection for improving resistance to VW in cotton.
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Affiliation(s)
- Tinggang Li
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Xuefeng Ma
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Nanyang Li
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Lei Zhou
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Zheng Liu
- Xinjiang Academy of Agricultural and Reclamation ScienceXinjiangChina
| | - Huanyong Han
- Xinjiang Academy of Agricultural and Reclamation ScienceXinjiangChina
| | - Yuejing Gui
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Yuming Bao
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Jieyin Chen
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
| | - Xiaofeng Dai
- Laboratory of Cotton DiseaseInstitute of Food Science and TechnologyChinese Academy of Agricultural SciencesBeijingChina
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25
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Singh A, Sharma V, Dikshit HK, Aski M, Kumar H, Thirunavukkarasu N, Patil BS, Kumar S, Sarker A. Association mapping unveils favorable alleles for grain iron and zinc concentrations in lentil (Lens culinaris subsp. culinaris). PLoS One 2017; 12:e0188296. [PMID: 29161321 PMCID: PMC5697819 DOI: 10.1371/journal.pone.0188296] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Accepted: 11/04/2017] [Indexed: 11/18/2022] Open
Abstract
Lentil is a major cool-season grain legume grown in South Asia, West Asia, and North Africa. Populations in developing countries of these regions have micronutrient deficiencies; therefore, breeding programs should focus more on improving the micronutrient content of food. In the present study, a set of 96 diverse germplasm lines were evaluated at three different locations in India to examine the variation in iron (Fe) and zinc (Zn) concentration and identify simple sequence repeat (SSR) markers that associate with the genetic variation. The genetic variation among genotypes of the association mapping (AM) panel was characterized using a genetic distance-based and a general model-based clustering method. The model-based analysis identified six subpopulations, which satisfactorily explained the genetic structure of the AM panel. AM analysis identified three SSRs (PBALC 13, PBALC 206, and GLLC 563) associated with grain Fe concentration explaining 9% to 11% of phenotypic variation and four SSRs (PBALC 353, SSR 317-1, PLC 62, and PBALC 217) were associated with grain Zn concentration explaining 14%, to 21% of phenotypic variation. These identified SSRs exhibited consistent performance across locations. These candidate SSRs can be used in marker-assisted genetic improvement for developing Fe and Zn fortified lentil varieties. Favorable alleles and promising genotypes identified in this study can be utilized for lentil biofortification.
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Affiliation(s)
- Akanksha Singh
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
- Department of Bioscience and Biotechnology, Banasthali University, Banasthali, Rajasthan, India
| | - Vinay Sharma
- Department of Bioscience and Biotechnology, Banasthali University, Banasthali, Rajasthan, India
| | - Harsh Kumar Dikshit
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Muraleedhar Aski
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Harish Kumar
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
- Punjab Agriculture University, RRS, Faridkot, Punjab, India
| | | | | | - Shiv Kumar
- ICARDA, B.P. 6299, Station Experiment, INRA-Quich, Rue Hafiane Cherkaoui Agdal, Rabat-Institutes, Rabat, Morocco
| | - Ashutosh Sarker
- South Asia and China Program (ICARDA), NASC Complex, New Delhi, India
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Abdullaev AA, Salakhutdinov IB, Egamberdiev SS, Khurshut EE, Rizaeva SM, Ulloa M, Abdurakhmonov IY. Genetic diversity, linkage disequilibrium, and association mapping analyses of Gossypium barbadense L. germplasm. PLoS One 2017; 12:e0188125. [PMID: 29136656 PMCID: PMC5685624 DOI: 10.1371/journal.pone.0188125] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 11/01/2017] [Indexed: 02/05/2023] Open
Abstract
Limited polymorphism and narrow genetic base, due to genetic bottleneck through historic domestication, highlight a need for comprehensive characterization and utilization of existing genetic diversity in cotton germplasm collections. In this study, 288 worldwide Gossypium barbadense L. cotton germplasm accessions were evaluated in two diverse environments (Uzbekistan and USA). These accessions were assessed for genetic diversity, population structure, linkage disequilibrium (LD), and LD-based association mapping (AM) of fiber quality traits using 108 genome-wide simple sequence repeat (SSR) markers. Analyses revealed structured population characteristics and a high level of intra-variability (67.2%) and moderate interpopulation differentiation (32.8%). Eight percent and 4.3% of markers revealed LD in the genome of the G. barbadense at critical values of r2 ≥ 0.1 and r2 ≥ 0.2, respectively. The LD decay was on average 24.8 cM at the threshold of r2 ≥ 0.05. LD retained on average distance of 3.36 cM at the threshold of r2 ≥ 0.1. Based on the phenotypic evaluations in the two diverse environments, 100 marker loci revealed a strong association with major fiber quality traits using mixed linear model (MLM) based association mapping approach. Fourteen marker loci were found to be consistent with previously identified quantitative trait loci (QTLs), and 86 were found to be new unreported marker loci. Our results provide insights into the breeding history and genetic relationship of G. barbadense germplasm and should be helpful for the improvement of cotton cultivars using molecular breeding and omics-based technologies.
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Affiliation(s)
- Alisher A. Abdullaev
- Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan
| | - Ilkhom B. Salakhutdinov
- Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan
| | - Sharof S. Egamberdiev
- Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan
| | - Ernest E. Khurshut
- Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan
| | - Sofiya M. Rizaeva
- Institute of Genetics and Plant Experimental Biology, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan
| | - Mauricio Ulloa
- Cropping Systems Research Laboratory, United States Department of Agriculture - Agricultural Research Services, Lubbock, Texas, United States of America
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27
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Huang C, Nie X, Shen C, You C, Li W, Zhao W, Zhang X, Lin Z. Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome-wide association study using high-density SNPs. PLANT BIOTECHNOLOGY JOURNAL 2017; 15:1374-1386. [PMID: 28301713 PMCID: PMC5633765 DOI: 10.1111/pbi.12722] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 03/08/2017] [Accepted: 03/10/2017] [Indexed: 05/18/2023]
Abstract
Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton-producing and cotton-consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome-wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high-density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single-nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty-eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high-resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.
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Affiliation(s)
- Cong Huang
- National Key Laboratory of Crop Genetic ImprovementCollege of Plant Sciences & TechnologyHuazhong Agricultural UniversityWuhanHubeiChina
| | - Xinhui Nie
- National Key Laboratory of Crop Genetic ImprovementCollege of Plant Sciences & TechnologyHuazhong Agricultural UniversityWuhanHubeiChina
- Key Laboratory of Oasis Ecology Agricultural of Xinjiang BingtuanAgricultural CollegeShihezi UniversityShiheziXinjiangChina
| | - Chao Shen
- National Key Laboratory of Crop Genetic ImprovementCollege of Plant Sciences & TechnologyHuazhong Agricultural UniversityWuhanHubeiChina
| | - Chunyuan You
- Cotton Research InstituteShihezi Academy of Agriculture ScienceShiheziXinjiangChina
| | - Wu Li
- Economic Crop Research InstituteHenan Academy of Agricultural SciencesZhengzhouHenanChina
| | - Wenxia Zhao
- National Key Laboratory of Crop Genetic ImprovementCollege of Plant Sciences & TechnologyHuazhong Agricultural UniversityWuhanHubeiChina
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic ImprovementCollege of Plant Sciences & TechnologyHuazhong Agricultural UniversityWuhanHubeiChina
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic ImprovementCollege of Plant Sciences & TechnologyHuazhong Agricultural UniversityWuhanHubeiChina
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28
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Zhao Y, Wang H, Chen W, Zhao P, Gong H, Sang X, Cui Y. Regional association analysis-based fine mapping of three clustered QTL for verticillium wilt resistance in cotton (G. hirsutum. L). BMC Genomics 2017; 18:661. [PMID: 28841857 PMCID: PMC6389109 DOI: 10.1186/s12864-017-4074-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Accepted: 08/16/2017] [Indexed: 11/21/2022] Open
Abstract
Background Verticillium wilt is one of the most destructive diseases affecting global cotton production. The most effective way to control wilt disease has been the development of new cotton varieties that are resistant to VW. VW-resistant Upland cotton cultivars have been created in both the USA and China by Gossypium barbadense introgression. More than 100 VW resistance quantitative trait loci have been detected. Results Three clustered VW resistance-related QTL were detected in a 120-line association population and assigned to a genome region of 14,653,469–55,190,112 bp in Dt_chr9. A regional association analysis-based fine-mapping strategy was developed to narrow down the confidence intervals of the above QTL. The estimated LD decay of the genome region of interest was much faster than those of the Dt_chr9 chromosome and the whole genome, suggesting the existence of a recombination hotspot. Thirty-seven haplotype blocks were detected. The confidence intervals of the three clustered QTL were narrowed down to a region of 937,906 bp involving QTL-i23734Gh and a region of 1,389,417 bp involving QTL- i10740Gh, respectively. Each region contained the strongest association signal. Comparative analysis redefined the confidence intervals of the other three QTLs, qDL52T2-c19, QTL-BNL4069, and QTL-JESPR0001. The broad-spectrum VW resistance QTL qVW-D9–1 was demonstrated to be closely linked with the three redefined QTL, QTL-i23734Gh, QTL- i10740Gh and QTL-JESPR0001. Twelve functional genes were detected to be located within the redefined confidence intervals of VW resistance QTL. The mRNA CotAD_60243, encoding E3 ubiquitin-protein ligase UPL2-like, responsible for plant innate immunity and broad-spectrum disease resistance, was found to be overlapped with the strongest association signal i10740Gh. Six mRNAs encoding putative disease-resistance proteins were within the redefined confidence interval of QTL-JESPR0001, suggesting a tandem arrangement of R genes. Conclusions Our results proved that the VW resistance effect related to three clustered VW resistance-related QTL was actually controled by two redefined major QTL and severlal minor loci. The broad-spectrum VW resistance QTL qVW-D9–1 may be closely linked with the two redefined major QTLs. The tandem arrangement of R genes were detected in the redefined confidence interval of QTL-JESPR0001. The candidate genes obtained should be helpful in identifying and characterizing defense genes related to VW resistance QTL. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-4074-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yunlei Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Hongmei Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China.
| | - Wei Chen
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Pei Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Haiyan Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Xiaohui Sang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
| | - Yanli Cui
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, Henan, 455000, China
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Ademe MS, He S, Pan Z, Sun J, Wang Q, Qin H, Liu J, Liu H, Yang J, Xu D, Yang J, Ma Z, Zhang J, Li Z, Cai Z, Zhang X, Zhang X, Huang A, Yi X, Zhou G, Li L, Zhu H, Pang B, Wang L, Jia Y, Du X. Association mapping analysis of fiber yield and quality traits in Upland cotton (Gossypium hirsutum L.). Mol Genet Genomics 2017; 292:1267-1280. [PMID: 28748394 DOI: 10.1007/s00438-017-1346-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Accepted: 06/29/2017] [Indexed: 12/15/2022]
Abstract
Fiber yield and quality are the most important traits for Upland cotton (Gossypium hirsutum L.). Identifying high yield and good fiber quality genes are the prime concern of researchers in cotton breeding. Association mapping offers an alternative and powerful method for detecting those complex agronomic traits. In this study, 198 simple sequence repeats (SSRs) were used to screen markers associated with fiber yield and quality traits with 302 elite Upland cotton accessions that were evaluated in 12 locations representing the Yellow River and Yangtze River cotton growing regions of China. Three subpopulations were found after the estimation of population structure. The pair-wise kinship values varied from 0 to 0.867. Only 1.59% of the total marker locus pairs showed significant linkage disequilibrium (LD, p < 0.001). The genome-wide LD decayed within the genetic distance of ~30 to 32 cM at r 2 = 0.1, and decreased to ~1 to 2 cM at r 2 = 0.2, indicating the potential for association mapping. Analysis based on a mixed linear model detected 57 significant (p < 0.01) marker-trait associations, including seven associations for fiber length, ten for fiber micronaire, nine for fiber strength, eight for fiber elongation, five for fiber uniformity index, five for fiber uniformity ratio, six for boll weight and seven for lint percent, for a total of 35 SSR markers, of which 11 markers were associated with more than one trait. Among marker-trait associations, 24 associations coincided with the previously reported quantitative trait loci (QTLs), the remainder were newly identified QTLs/genes. The QTLs identified in this study will potentially facilitate improvement of fiber yield and quality in the future cotton molecular breeding programs.
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Affiliation(s)
- Mulugeta Seyoum Ademe
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China
| | - Shoupu He
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China
| | - Zhaoe Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China
| | - Junling Sun
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China
| | - Qinglian Wang
- Henan Institute of Science and Technology, Xinxiang, China
| | - Hongde Qin
- Cash Crop Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Jinhai Liu
- Zhongmian Cotton Seed Industry Technology Co., Ltd, Zhengzhou, China
| | - Hui Liu
- Jing Hua Seed Industry Technologies Inc, Jingzhou, China
| | - Jun Yang
- Cotton Research Institute of Jiangxi Province, Jiujiang, China
| | - Dongyong Xu
- Guoxin Rural Technical Service Association, Hebei, China
| | - Jinlong Yang
- Zhongmian Cotton Seed Industry Technology Co., Ltd, Zhengzhou, China
| | - Zhiying Ma
- Key Laboratory of Crop Germplasm Resources of Hebei, Agricultural University of Hebei, Baoding, China
| | | | - Zhikun Li
- Key Laboratory of Crop Germplasm Resources of Hebei, Agricultural University of Hebei, Baoding, China
| | - Zhongmin Cai
- Zhongmian Cotton Seed Industry Technology Co., Ltd, Zhengzhou, China
| | | | - Xin Zhang
- Henan Institute of Science and Technology, Xinxiang, China
| | - Aifen Huang
- Sanyi Seed Industry of Changde in Hunan Inc, Changde, China
| | - Xianda Yi
- Cash Crop Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Guanyin Zhou
- Zhongmian Cotton Seed Industry Technology Co., Ltd, Zhengzhou, China
| | - Lin Li
- Zhongli Company of Shandong, Shandong, China
| | - Haiyong Zhu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China
| | - Baoyin Pang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China
| | - Liru Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China
| | - Yinhua Jia
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China.
| | - Xiongming Du
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), P. O. Box 455000, Anyang, Henan, China.
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Liu X, Teng Z, Wang J, Wu T, Zhang Z, Deng X, Fang X, Tan Z, Ali I, Liu D, Zhang J, Liu D, Liu F, Zhang Z. Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.). Mol Genet Genomics 2017; 292:1281-1306. [PMID: 28733817 DOI: 10.1007/s00438-017-1347-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 06/29/2017] [Indexed: 10/19/2022]
Abstract
Cotton is a significant commercial crop that plays an indispensable role in many domains. Constructing high-density genetic maps and identifying stable quantitative trait locus (QTL) controlling agronomic traits are necessary prerequisites for marker-assisted selection (MAS). A total of 14,899 SSR primer pairs designed from the genome sequence of G. raimondii were screened for polymorphic markers between mapping parents CCRI 35 and Yumian 1, and 712 SSR markers showing polymorphism were used to genotype 180 lines from a (CCRI 35 × Yumian 1) recombinant inbred line (RIL) population. Genetic linkage analysis was conducted on 726 loci obtained from the 712 polymorphic SSR markers, along with 1379 SSR loci obtained in our previous study, and a high-density genetic map with 2051 loci was constructed, which spanned 3508.29 cM with an average distance of 1.71 cM between adjacent markers. Marker orders on the linkage map are highly consistent with the corresponding physical orders on a G. hirsutum genome sequence. Based on fiber quality and yield component trait data collected from six environments, 113 QTLs were identified through two analytical methods. Among these 113 QTLs, 50 were considered stable (detected in multiple environments or for which phenotypic variance explained by additive effect was greater than environment effect), and 18 of these 50 were identified with stability by both methods. These 18 QTLs, including eleven for fiber quality and seven for yield component traits, could be priorities for MAS.
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Affiliation(s)
- Xueying Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhonghua Teng
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Jinxia Wang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Tiantian Wu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhiqin Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Xianping Deng
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Xiaomei Fang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Zhaoyun Tan
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Iftikhar Ali
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Dexin Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Jian Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Dajun Liu
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China
| | - Fang Liu
- State Key Laboratory of Cotton Biology/Cotton Research Institute, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
| | - Zhengsheng Zhang
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Southwest University, Chongqing, 400716, China.
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Cai C, Wu S, Niu E, Cheng C, Guo W. Identification of genes related to salt stress tolerance using intron-length polymorphic markers, association mapping and virus-induced gene silencing in cotton. Sci Rep 2017; 7:528. [PMID: 28373664 PMCID: PMC5428780 DOI: 10.1038/s41598-017-00617-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 03/06/2017] [Indexed: 12/20/2022] Open
Abstract
Intron length polymorphisms (ILPs), a type of gene-based functional marker, could themselves be related to the particular traits. Here, we developed a genome-wide cotton ILPs based on orthologs annotation from two sequenced diploid species, A-genome Gossypium arboreum and D-genome G. raimondii. We identified 10,180 putative ILP markers from 5,021 orthologous genes. Among these, 535 ILP markers from 9 gene families related to stress were selected for experimental verification. Polymorphic rates were 72.71% between G. arboreum and G. raimondii and 36.45% between G. hirsutum acc. TM-1 and G. barbadense cv. Hai7124. Furthermore, 14 polymorphic ILP markers were detected in 264 G. hirsutum accessions. Coupled with previous simple sequence repeats (SSRs) evaluations and salt tolerance assays from the same individuals, we found a total of 25 marker-trait associations involved in nine ILPs. The nine genes, temporally named as C1 to C9, showed the various expressions in different organs and tissues, and five genes (C3, C4, C5, C7 and C9) were significantly upregulated after salt treatment. We verified that the five genes play important roles in salt tolerance. Particularly, silencing of C4 (encodes WRKY DNA-binding protein) and C9 (encodes Mitogen-activated protein kinase) can significantly enhance cotton susceptibility to salt stress.
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Affiliation(s)
- Caiping Cai
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Shuang Wu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Erli Niu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Chaoze Cheng
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Wangzhen Guo
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China.
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Fang L, Gong H, Hu Y, Liu C, Zhou B, Huang T, Wang Y, Chen S, Fang DD, Du X, Chen H, Chen J, Wang S, Wang Q, Wan Q, Liu B, Pan M, Chang L, Wu H, Mei G, Xiang D, Li X, Cai C, Zhu X, Chen ZJ, Han B, Chen X, Guo W, Zhang T, Huang X. Genomic insights into divergence and dual domestication of cultivated allotetraploid cottons. Genome Biol 2017; 18:33. [PMID: 28219438 PMCID: PMC5317056 DOI: 10.1186/s13059-017-1167-5] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2016] [Accepted: 02/06/2017] [Indexed: 11/10/2022] Open
Abstract
Background Cotton has been cultivated and used to make fabrics for at least 7000 years. Two allotetraploid species of great commercial importance, Gossypium hirsutum and Gossypium barbadense, were domesticated after polyploidization and are cultivated worldwide. Although the overall genetic diversity between these two cultivated species has been studied with limited accessions, their population structure and genetic variations remain largely unknown. Results We resequence the genomes of 147 cotton accessions, including diverse wild relatives, landraces, and modern cultivars, and construct a comprehensive variation map to provide genomic insights into the divergence and dual domestication of these two important cultivated tetraploid cotton species. Phylogenetic analysis shows two divergent groups for G. hirsutum and G. barbadense, suggesting a dual domestication processes in tetraploid cottons. In spite of the strong genetic divergence, a small number of interspecific reciprocal introgression events are found between these species and the introgression pattern is significantly biased towards the gene flow from G. hirsutum into G. barbadense. We identify selective sweeps, some of which are associated with relatively highly expressed genes for fiber development and seed germination. Conclusions We report a comprehensive analysis of the evolution and domestication history of allotetraploid cottons based on the whole genomic variation between G. hirsutum and G. barbadense and between wild accessions and modern cultivars. These results provide genomic bases for improving cotton production and for further evolution analysis of polyploid crops. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1167-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Lei Fang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Hao Gong
- National Center for Gene Research, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Yan Hu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Chunxiao Liu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Baoliang Zhou
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Tao Huang
- National Center for Gene Research, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Yangkun Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Shuqi Chen
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - David D Fang
- Cotton Fiber Bioscience Research Unit, USDA-ARS-SRRC, New Orleans, LA, 70124, USA
| | - Xiongming Du
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Hong Chen
- Cotton Research Institute, Xinjiang Academy of Agriculture and Reclamation Sciences, Xinjiang, 832000, China
| | - Jiedan Chen
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Sen Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Qiong Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Qun Wan
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Bingliang Liu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Mengqiao Pan
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Lijing Chang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Huaitong Wu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Gaofu Mei
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Dan Xiang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Xinghe Li
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Caiping Cai
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Xiefei Zhu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Z Jeffrey Chen
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China.,Department of Molecular Biosciences, Center for Computational Biology and Bioinformatics, and Institute for Cellular and Molecular Biology, the University of Texas at Austin, Austin, TX, 78712, USA
| | - Bin Han
- National Center for Gene Research, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Xiaoya Chen
- State Key Laboratory of Plant Molecular Genetics, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200032, China
| | - Wangzhen Guo
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China
| | - Tianzhen Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Hybrid R & D Engineering Center (the Ministry of Education), Nanjing Agricultural University, Nanjing, 210095, China. .,Agronomy Department, College of Agriculture and Biotechnology, Zhejiang University, Zhejiang, 310029, China.
| | - Xuehui Huang
- National Center for Gene Research, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200233, China. .,College of life and environmental sciences, Shanghai Normal University, Shanghai, 200234, China.
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Iqbal MA, Rahman MU. Identification of Marker-Trait Associations for Lint Traits in Cotton. FRONTIERS IN PLANT SCIENCE 2017; 8:86. [PMID: 28220132 PMCID: PMC5292784 DOI: 10.3389/fpls.2017.00086] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2016] [Accepted: 01/16/2017] [Indexed: 05/20/2023]
Abstract
Harvesting high quality lint, a long-awaited breeding goal-accomplished partly, can be achieved by identifying DNA markers which could be used for diagnosing cotton plants containing the desired traits. In the present studies, a total of 185 cotton genotypes exhibiting diversity for lint traits were selected from a set of 546 genotypes evaluated for fiber traits in 2009. These genotypes were extensively studied for three consecutive years (2011-2013) at three different locations. Significant genetic variations were found for average boll weight, ginning out turn (GOT), micronaire value, staple length, fiber bundle strength, and uniformity index. IR-NIBGE-3701 showed maximum GOT (43.63%). Clustering of genotypes using Ward's method was found more informative than that of the clusters generated by principal component analysis. A total of 382 SSRs were surveyed on 10 Gossypium hirsutum genotypes exhibiting contrasting fiber traits. Out of these, 95 polymorphic SSR primer pairs were then surveyed on 185 genotypes. The gene diversity averaged 0.191 and the polymorphic information content (PIC) averaged 0.175. Unweighted pair group method with arithmetic mean (UPGMA), principal coordinate analysis (PCoA), and STRUCTURE software grouped these genotypes into four major clusters each. Genetic distance within the clusters ranged from 0.0587 to 0.1030. A total of 47 (25.41%) genotypes exhibited shared ancestry. In total 6.8% (r2 ≥ 0.05) and 4.4% (r2 ≥ 0.1) of the marker pairs showed significant linkage disequilibrium (LD). A number of marker-trait associations (in total 75) including 13 for average boll weight, 18 for GOT percentage, eight for micronaire value, 18 for staple length, three for fiber bundle strength, and 15 for uniformity index were calculated. Out of these, MGHES-51 was associated with all the traits. Most of the marker-trait associations were novel while few validated the associations reported in the previous studies. High frequency of favorable alleles in cultivated varieties is possibly due to fixation of desirable alleles by domestication. These favorable alleles can be used in marker assisted breeding or for gene cloning using next generation sequencing tools. The present studies would set a stage for harvesting high quality lint without compromising the yield potential-ascertaining natural fiber security.
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Affiliation(s)
- Muhammad A. Iqbal
- Plant Genomics and Molecular Breeding Lab (PGMB), Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE)Faisalabad, Pakistan
- Department of Biotechnology, Pakistan Institute of Engineering and Applied Sciences (PIEAS)Nilore, Islamabad, Pakistan
| | - Mehboob-ur- Rahman
- Plant Genomics and Molecular Breeding Lab (PGMB), Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE)Faisalabad, Pakistan
- Department of Biotechnology, Pakistan Institute of Engineering and Applied Sciences (PIEAS)Nilore, Islamabad, Pakistan
- *Correspondence: Mehboob-ur-Rahman ;
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Anuradha N, Satyavathi CT, Bharadwaj C, Nepolean T, Sankar SM, Singh SP, Meena MC, Singhal T, Srivastava RK. Deciphering Genomic Regions for High Grain Iron and Zinc Content Using Association Mapping in Pearl Millet. FRONTIERS IN PLANT SCIENCE 2017; 8:412. [PMID: 28507551 PMCID: PMC5410614 DOI: 10.3389/fpls.2017.00412] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Accepted: 03/10/2017] [Indexed: 05/11/2023]
Abstract
Micronutrient malnutrition, especially deficiency of two mineral elements, iron [Fe] and zinc [Zn] in the developing world needs urgent attention. Pearl millet is one of the best crops with many nutritional properties and is accessible to the poor. We report findings of the first attempt to mine favorable alleles for grain iron and zinc content through association mapping in pearl millet. An association mapping panel of 130 diverse lines was evaluated at Delhi, Jodhpur and Dharwad, representing all the three pearl millet growing agro-climatic zones of India, during 2014 and 2015. Wide range of variation was observed for grain iron (32.3-111.9 ppm) and zinc (26.6-73.7 ppm) content. Genotyping with 114 representative polymorphic SSRs revealed 0.35 mean gene diversity. STRUCTURE analysis revealed presence of three sub-populations which was further supported by Neighbor-Joining method of clustering and principal coordinate analysis (PCoA). Marker-trait associations (MTAs) were analyzed with 267 markers (250 SSRs and 17 genic markers) in both general linear model (GLM) and mixed linear model (MLM), however, MTAs resulting from MLM were considered for more robustness of the associations. After appropriate Bonferroni correction, Xpsmp 2261 (13.34% R2-value), Xipes 0180 (R2-value of 11.40%) and Xipes 0096 (R2-value of 11.38%) were consistently associated with grain iron and zinc content for all the three locations. Favorable alleles and promising lines were identified for across and specific environments. PPMI 1102 had highest number (7) of favorable alleles, followed by four each for PPMFeZMP 199 and PPMI 708 for across the environment performance for both grain Fe and Zn content, while PPMI 1104 had alleles specific to Dharwad for grain Fe and Zn content. When compared with the reference genome Tift 23D2B1-P1-P5, Xpsmp 2261 amplicon was identified in intergenic region on pseudomolecule 5, while the other marker, Xipes 0810 was observed to be overlapping with aspartic proteinase (Asp) gene on pseudomolecule 3. Thus, this study can help in breeding new lines with enhanced micronutrient content using marker-assisted selection (MAS) in pearl millet leading to improved well-being especially for women and children.
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Affiliation(s)
- N. Anuradha
- Division of Genetics, ICAR-Indian Agricultural Research InstituteNew Delhi, India
| | - C. Tara Satyavathi
- Division of Genetics, ICAR-Indian Agricultural Research InstituteNew Delhi, India
- *Correspondence: C. Tara Satyavathi
| | - C. Bharadwaj
- Division of Genetics, ICAR-Indian Agricultural Research InstituteNew Delhi, India
| | - T. Nepolean
- Division of Genetics, ICAR-Indian Agricultural Research InstituteNew Delhi, India
| | - S. Mukesh Sankar
- Division of Genetics, ICAR-Indian Agricultural Research InstituteNew Delhi, India
| | - Sumer P. Singh
- Division of Genetics, ICAR-Indian Agricultural Research InstituteNew Delhi, India
| | - Mahesh C. Meena
- Division of Soil Science and Agricultural Chemistry, ICAR-Indian Agricultural Research InstituteNew Delhi, India
| | - Tripti Singhal
- Division of Genetics, ICAR-Indian Agricultural Research InstituteNew Delhi, India
| | - Rakesh K. Srivastava
- International Crops Research Institute for the Semi-Arid TropicsPatancheru, India
- Rakesh K. Srivastava
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Two genomic regions associated with fiber quality traits in Chinese upland cotton under apparent breeding selection. Sci Rep 2016; 6:38496. [PMID: 27924947 PMCID: PMC5141495 DOI: 10.1038/srep38496] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Accepted: 11/11/2016] [Indexed: 01/28/2023] Open
Abstract
Fiber quality is one of the most important agronomic traits of cotton, and understanding the genetic basis of its target traits will accelerate improvements to cotton fiber quality. In this study, a panel comprising 355 upland cotton accessions was used to perform genome-wide association studies (GWASs) of five fiber quality traits in four environments. A total of 16, 10 and 7 SNPs were associated with fiber length (FL), fiber strength (FS) and fiber uniformity (FU), respectively, based on the mixed linear model (MLM). Most importantly, two major genomic regions (MGR1 and MGR2) on chromosome Dt7 and four potential candidate genes for FL were identified. Analyzing the geographical distribution of favorable haplotypes (FHs) among these lines revealed that two favorable haplotype frequencies (FHFs) were higher in accessions from low-latitude regions than in accessions from high-latitude regions. However, the genetic diversity of lines from the low-latitude regions was lower than the diversity of lines from the high-latitude regions in China. Furthermore, the FHFs differed among cultivars developed during different breeding periods. These results indicate that FHs have undergone artificial selection during upland cotton breeding in recent decades in China and provide a foundation for the further improvement of fiber quality traits.
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Islam MS, Thyssen GN, Jenkins JN, Zeng L, Delhom CD, McCarty JC, Deng DD, Hinchliffe DJ, Jones DC, Fang DD. A MAGIC population-based genome-wide association study reveals functional association of GhRBB1_A07 gene with superior fiber quality in cotton. BMC Genomics 2016; 17:903. [PMID: 27829353 PMCID: PMC5103610 DOI: 10.1186/s12864-016-3249-2] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Accepted: 11/02/2016] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Cotton supplies a great majority of natural fiber for the global textile industry. The negative correlation between yield and fiber quality has hindered breeders' ability to improve these traits simultaneously. A multi-parent advanced generation inter-cross (MAGIC) population developed through random-mating of multiple diverse parents has the ability to break this negative correlation. Genotyping-by-sequencing (GBS) is a method that can rapidly identify and genotype a large number of single nucleotide polymorphisms (SNP). Genotyping a MAGIC population using GBS technologies will enable us to identify marker-trait associations with high resolution. RESULTS An Upland cotton MAGIC population was developed through random-mating of 11 diverse cultivars for five generations. In this study, fiber quality data obtained from four environments and 6071 SNP markers generated via GBS and 223 microsatellite markers of 547 recombinant inbred lines (RILs) of the MAGIC population were used to conduct a genome wide association study (GWAS). By employing a mixed linear model, GWAS enabled us to identify markers significantly associated with fiber quantitative trait loci (QTL). We identified and validated one QTL cluster associated with four fiber quality traits [short fiber content (SFC), strength (STR), length (UHM) and uniformity (UI)] on chromosome A07. We further identified candidate genes related to fiber quality attributes in this region. Gene expression and amino acid substitution analysis suggested that a regeneration of bulb biogenesis 1 (GhRBB1_A07) gene is a candidate for superior fiber quality in Upland cotton. The DNA marker CFBid0004 designed from an 18 bp deletion in the coding sequence of GhRBB1_A07 in Acala Ultima is associated with the improved fiber quality in the MAGIC RILs and 105 additional commercial Upland cotton cultivars. CONCLUSION Using GBS and a MAGIC population enabled more precise fiber QTL mapping in Upland cotton. The fiber QTL and associated markers identified in this study can be used to improve fiber quality through marker assisted selection or genomic selection in a cotton breeding program. Target manipulation of the GhRBB1_A07 gene through biotechnology or gene editing may potentially improve cotton fiber quality.
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Affiliation(s)
- Md Sariful Islam
- Cotton Fiber Bioscience Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA 70124 USA
| | - Gregory N. Thyssen
- Cotton Chemistry and Utilization Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA 70124 USA
| | - Johnie N. Jenkins
- Genetics & Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS 39762 USA
| | - Linghe Zeng
- Crop Genetics Research Unit, USDA-ARS, Stoneville, MS 38772 USA
| | - Christopher D. Delhom
- Cotton Structure and Quality Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA 70124 USA
| | - Jack C. McCarty
- Genetics & Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS 39762 USA
| | - Dewayne D. Deng
- Genetics & Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS 39762 USA
| | - Doug J. Hinchliffe
- Cotton Chemistry and Utilization Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA 70124 USA
| | | | - David D. Fang
- Cotton Fiber Bioscience Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA 70124 USA
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Su J, Pang C, Wei H, Li L, Liang B, Wang C, Song M, Wang H, Zhao S, Jia X, Mao G, Huang L, Geng D, Wang C, Fan S, Yu S. Identification of favorable SNP alleles and candidate genes for traits related to early maturity via GWAS in upland cotton. BMC Genomics 2016; 17:687. [PMID: 27576450 PMCID: PMC5006539 DOI: 10.1186/s12864-016-2875-z] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 07/05/2016] [Indexed: 11/17/2022] Open
Abstract
Background Early maturity is one of the most important and complex agronomic traits in upland cotton (Gossypium hirsutum L). To dissect the genetic architecture of this agronomically important trait, a population consisting of 355 upland cotton germplasm accessions was genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) approach, of which a subset of 185 lines representative of the diversity among the accessions was phenotypically characterized for six early maturity traits in four environments. A genome-wide association study (GWAS) was conducted using the generalized linear model (GLM) and mixed linear model (MLM). Results A total of 81,675 SNPs in 355 upland cotton accessions were discovered using SLAF-seq and were subsequently used in GWAS. Thirteen significant associations between eight SNP loci and five early maturity traits were successfully identified using the GLM and MLM; two of the 13 associations were common between the models. By computing phenotypic effect values for the associations detected at each locus, 11 highly favorable SNP alleles were identified for five early maturity traits. Moreover, dosage pyramiding effects of the highly favorable SNP alleles and significant linear correlations between the numbers of highly favorable alleles and the phenotypic values of the target traits were identified. Most importantly, a major locus (rs13562854) on chromosome Dt3 and a potential candidate gene (CotAD_01947) for early maturity were detected. Conclusions This study identified highly favorable SNP alleles and candidate genes associated with early maturity traits in upland cotton. The results demonstrate that GWAS is a powerful tool for dissecting complex traits and identifying candidate genes. The highly favorable SNP alleles and candidate genes for early maturity traits identified in this study should be show high potential for improvement of early maturity in future cotton breeding programs. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2875-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Junji Su
- College of Agronomy, Northwest A&F University, Yangling, China.,State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China.,Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, Xinjiang, China
| | - Chaoyou Pang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Hengling Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Libei Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Bing Liang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Caixiang Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Meizhen Song
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Hantao Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Shuqi Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xiaoyun Jia
- College of Agronomy, Northwest A&F University, Yangling, China.,State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Guangzhi Mao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Long Huang
- Bioinformatics Division, Biomarker Technologies Corporation, Beijing, China
| | - Dandan Geng
- Bioinformatics Division, Biomarker Technologies Corporation, Beijing, China
| | - Chengshe Wang
- College of Agronomy, Northwest A&F University, Yangling, China.
| | - Shuli Fan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China.
| | - Shuxun Yu
- College of Agronomy, Northwest A&F University, Yangling, China. .,State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China.
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Islam MS, Zeng L, Thyssen GN, Delhom CD, Kim HJ, Li P, Fang DD. Mapping by sequencing in cotton (Gossypium hirsutum) line MD52ne identified candidate genes for fiber strength and its related quality attributes. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2016; 129:1071-86. [PMID: 26883043 DOI: 10.1007/s00122-016-2684-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2015] [Accepted: 01/23/2016] [Indexed: 05/22/2023]
Abstract
Three QTL regions controlling three fiber quality traits were validated and further fine-mapped with 27 new single nucleotide polymorphism (SNP) markers. Transcriptome analysis suggests that receptor-like kinases found within the validated QTLs are potential candidate genes responsible for superior fiber strength in cotton line MD52ne. Fiber strength, length, maturity and fineness determine the market value of cotton fibers and the quality of spun yarn. Cotton fiber strength has been recognized as a critical quality attribute in the modern textile industry. Fine mapping along with quantitative trait loci (QTL) validation and candidate gene prediction can uncover the genetic and molecular basis of fiber quality traits. Four previously-identified QTLs (qFBS-c3, qSFI-c14, qUHML-c14 and qUHML-c24) related to fiber bundle strength, short fiber index and fiber length, respectively, were validated using an F3 population that originated from a cross of MD90ne × MD52ne. A group of 27 new SNP markers generated from mapping-by-sequencing (MBS) were placed in QTL regions to improve and validate earlier maps. Our refined QTL regions spanned 4.4, 1.8 and 3.7 Mb of physical distance in the Gossypium raimondii reference genome. We performed RNA sequencing (RNA-seq) of 15 and 20 days post-anthesis fiber cells from MD52ne and MD90ne and aligned reads to the G. raimondii genome. The QTL regions contained 21 significantly differentially expressed genes (DEGs) between the two near-isogenic parental lines. SNPs that result in non-synonymous substitutions to amino acid sequences of annotated genes were identified within these DEGs, and mapped. Taken together, transcriptome and amino acid mutation analysis indicate that receptor-like kinase pathway genes are likely candidates for superior fiber strength and length in MD52ne. MBS along with RNA-seq demonstrated a powerful strategy to elucidate candidate genes for the QTLs that control complex traits in a complex genome like tetraploid upland cotton.
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Affiliation(s)
- Md S Islam
- Cotton Fiber Bioscience Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA, 70124, USA
| | - Linghe Zeng
- Crop Genetics Research Unit, USDA-ARS, 141 Experiment Station Road, Stoneville, MS, 38772, USA
| | - Gregory N Thyssen
- Cotton Chemistry and Utilization Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA, 70124, USA
| | - Christopher D Delhom
- Cotton Structure and Quality Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA, 70124, USA
| | - Hee Jin Kim
- Cotton Fiber Bioscience Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA, 70124, USA
| | - Ping Li
- Cotton Fiber Bioscience Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA, 70124, USA
| | - David D Fang
- Cotton Fiber Bioscience Research Unit, USDA-ARS, Southern Regional Research Center, New Orleans, LA, 70124, USA.
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Egamberdiev SS, Saha S, Salakhutdinov I, Jenkins JN, Deng D, Y Abdurakhmonov I. Comparative assessment of genetic diversity in cytoplasmic and nuclear genome of upland cotton. Genetica 2016; 144:289-306. [PMID: 27155886 DOI: 10.1007/s10709-016-9898-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2015] [Accepted: 04/07/2016] [Indexed: 02/05/2023]
Abstract
The importance of the cytoplasmic genome for many economically important traits is well documented in several crop species, including cotton. There is no report on application of cotton chloroplast specific SSR markers as a diagnostic tool to study genetic diversity among improved Upland cotton lines. The complete plastome sequence information in GenBank provided us an opportunity to report on 17 chloroplast specific SSR markers using a cost-effective data mining strategy. Here we report the comparative analysis of genetic diversity among a set of 42 improved Upland cotton lines using SSR markers specific to chloroplast and nuclear genome, respectively. Our results revealed that low to moderate level of genetic diversity existed in both nuclear and cytoplasm genome among this set of cotton lines. However, the specific estimation suggested that genetic diversity is lower in cytoplasmic genome compared to the nuclear genome among this set of Upland cotton lines. In summary, this research is important from several perspectives. We detected a set of cytoplasm genome specific SSR primer pairs by using a cost-effective data mining strategy. We reported for the first time the genetic diversity in the cytoplasmic genome within a set of improved Upland cotton accessions. Results revealed that the genetic diversity in cytoplasmic genome is narrow, compared to the nuclear genome within this set of Upland cotton accessions. Our results suggested that most of these polymorphic chloroplast SSRs would be a valuable complementary tool in addition to the nuclear SSR in the study of evolution, gene flow and genetic diversity in Upland cotton.
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Affiliation(s)
- Sharof S Egamberdiev
- Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan, 111215
| | - Sukumar Saha
- Crop Science Research Laboratory, Genetics and Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS, 39762, USA.
| | - Ilkhom Salakhutdinov
- Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan, 111215
| | - Johnie N Jenkins
- Crop Science Research Laboratory, Genetics and Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS, 39762, USA
| | - Dewayne Deng
- Crop Science Research Laboratory, Genetics and Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS, 39762, USA
| | - Ibrokhim Y Abdurakhmonov
- Center of Genomics and Bioinformatics, Academy of Sciences of Uzbekistan, Tashkent, Uzbekistan, 111215
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Nie X, Huang C, You C, Li W, Zhao W, Shen C, Zhang B, Wang H, Yan Z, Dai B, Wang M, Zhang X, Lin Z. Genome-wide SSR-based association mapping for fiber quality in nation-wide upland cotton inbreed cultivars in China. BMC Genomics 2016; 17:352. [PMID: 27177443 PMCID: PMC4866303 DOI: 10.1186/s12864-016-2662-x] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 04/23/2016] [Indexed: 12/04/2022] Open
Abstract
Background Since upland cotton was introduced into China during the 1920s–1950s, hundreds of inbreed cultivars have been developed. To explore the molecular diversity, population structure and elite alleles, 503 inbred cultivars developed in China and some foreign cultivars from the United States and the Soviet Union were collected and analyzed by 494 genome-wide SSRs (Simple Sequence Repeats). Methods Four hundred and ninety-four pairs of SSRs with high polymorphism and uniform distribution on 26 chromosomes were used to scan polymorphisms in 503 nation-wide upland cottons. The programming language R was used to make boxplots for the phenotypic traits in different environments. Molecular marker data and 6 fiber quality traits were analyzed by the method of MLM (mixed linear model) (P + G + Q + K) in the TASSEL software package on the basis of the population structure and linkage disequilibrium analysis. The loci of elite allelic variation and typical materials carrying elite alleles were identified based on phenotypic effect values. Results A total of 179 markers were polymorphic and generated 426 allele loci; the population based on molecular diversity was classified into seven subpopulations corresponding to pedigree origin, ecological and geographical distribution. The attenuation distance of linkage disequilibrium dropped significantly up to 0–5 cM. Association mapping for fiber quality showed that 216 marker loci were associated with fiber quality traits (P < 0.05) explaining 0.58 % ~ 5.12 % of the phenotypic variation, with an average of 2.70 %. Thirteen marker loci were coincident with other studies, and three were detected for the same trait. Seven quantitative trait loci were related to known genes in fiber development. Based on phenotypic effects, 48 typical materials that contained the elite allele loci related to fiber quality traits were identified and are widely used in practical breeding. Conclusions The molecular diversity and population structure of 503 nation-wide upland cottons in China were evaluated by 494 genome-wide SSRs, and association mapping for fiber quality revealed known and novel elite alleles. The molecular diversity provides a guide for parental mating in cotton breeding, and the association mapping results will aid in the fine-mapping genes related to fiber quality traits and facilitate further studies on candidate genes. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2662-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xinhui Nie
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.,Cotton Research Institute, Shihezi Academy of Agriculture Science, Shihezi, 832011, Xinjiang, China
| | - Cong Huang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Chunyuan You
- Cotton Research Institute, Shihezi Academy of Agriculture Science, Shihezi, 832011, Xinjiang, China
| | - Wu Li
- Economic Crop Research Institute, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, Henan, China
| | - Wenxia Zhao
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Chao Shen
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Beibei Zhang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Hantao Wang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Zhenhua Yan
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Baoshen Dai
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Maojun Wang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
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Niu E, Cai C, Zheng Y, Shang X, Fang L, Guo W. Genome-wide analysis of CrRLK1L gene family in Gossypium and identification of candidate CrRLK1L genes related to fiber development. Mol Genet Genomics 2016; 291:1137-54. [PMID: 26833484 DOI: 10.1007/s00438-016-1169-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Accepted: 01/18/2016] [Indexed: 10/22/2022]
Abstract
Members of the CrRLK1L family, a subgroup of the receptor-like kinase (RLK) gene family, are thought to act as sensors for the integrity of the cell wall and regulators of polar elongation. To better understand the various functions in fiber development, we conducted genome-wide identification and characterization analyses of CrRLK1L family in cotton. Here 44, 40, and 79 CrRLK1L genes were identified from three cotton species: diploid G. raimondii (D5), diploid G. arboreum (A2), and tetraploid G. hirsutum TM-1 (AD1), respectively. The 44 CrRLK1Ls in G. raimondii were anchored to the 12 chromosomes unevenly and were classified into six groups (I-VI), with group II and group IV being further divided into two subgroups (groups IIa and IIb, and IVa and IVb, respectively). These CrRLK1Ls displayed a highly regular pattern of developmental and spatial regulation in cotton. Using the transcriptome data of five chromosomal segment introgression lines (CSILs) and the physical integration of CrRLK1Ls with the quantitative trait loci (QTLs) related to fiber quality traits, we revealed that six CrRLK1L genes were highly associated with fiber development. This study brings new insights into the integrated genome-wide identification of CrRLK1Ls in cotton and provides references for the genetic improvement of cotton fiber.
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Affiliation(s)
- Erli Niu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Caiping Cai
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yongjie Zheng
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xiaoguang Shang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Lei Fang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China
| | - Wangzhen Guo
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Hybrid Cotton R&D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, 210095, China.
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Su J, Fan S, Li L, Wei H, Wang C, Wang H, Song M, Zhang C, Gu L, Zhao S, Mao G, Wang C, Pang C, Yu S. Detection of Favorable QTL Alleles and Candidate Genes for Lint Percentage by GWAS in Chinese Upland Cotton. FRONTIERS IN PLANT SCIENCE 2016; 7:1576. [PMID: 27818672 PMCID: PMC5073211 DOI: 10.3389/fpls.2016.01576] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 10/06/2016] [Indexed: 05/18/2023]
Abstract
Improving cotton yield is a major breeding goal for Chinese upland cotton. Lint percentage is an important yield component and a critical economic index for cotton cultivars, and raising the lint percentage has a close relationship to improving cotton lint yield. To investigate the genetic architecture of lint percentage, a diversity panel consisting of 355 upland cotton accessions was grown, and the lint percentage was measured in four different environments. Genotyping was performed with specific-locus amplified fragment sequencing (SLAF-seq). Twelve single-nucleotide polymorphisms (SNPs) associated with lint percentage were detected via a genome-wide association study (GWAS), in which five SNP loci distributed on chromosomes At3 (A02) and At4 (A08) and contained two major-effect QTLs, which were detected in the best linear unbiased predictions (BLUPs) and in more than three environments simultaneously. Furthermore, favorable haplotypes (FHs) of two major-effect QTLs and 47 putative candidate genes in the two linkage disequilibrium (LD) blocks of these associated loci were identified. The expression levels of these putative candidate genes were estimated using RNA-seq data from ten upland cotton tissues. We found that Gh_A02G1268 was very highly expressed during the early fiber development stage, whereas the gene was poorly expressed in the seed. These results implied that Gh_A02G1268 may determine the lint percentage by regulating seed and fiber development. The favorable QTL alleles and candidate genes for lint percentage identified in this study will have high potential for improving lint yield in future Chinese cotton breeding programs.
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Affiliation(s)
- Junji Su
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
- Department of Plant Sciences, College of Agronomy, Northwest A&F UniversityYangling, China
| | - Shuli Fan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Libei Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Hengling Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Caixiang Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Hantao Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Meizhen Song
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Chi Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Lijiao Gu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Shuqi Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Guangzhi Mao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Chengshe Wang
- Department of Plant Sciences, College of Agronomy, Northwest A&F UniversityYangling, China
| | - Chaoyou Pang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
- *Correspondence: Chaoyou Pang
| | - Shuxun Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
- Department of Plant Sciences, College of Agronomy, Northwest A&F UniversityYangling, China
- Shuxun Yu
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Niu E, Shang X, Cheng C, Bao J, Zeng Y, Cai C, Du X, Guo W. Comprehensive Analysis of the COBRA-Like (COBL) Gene Family in Gossypium Identifies Two COBLs Potentially Associated with Fiber Quality. PLoS One 2015; 10:e0145725. [PMID: 26710066 PMCID: PMC4692504 DOI: 10.1371/journal.pone.0145725] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2015] [Accepted: 12/08/2015] [Indexed: 12/28/2022] Open
Abstract
COBRA-Like (COBL) genes, which encode a plant-specific glycosylphosphatidylinositol (GPI) anchored protein, have been proven to be key regulators in the orientation of cell expansion and cellulose crystallinity status. Genome-wide analysis has been performed in A. thaliana, O. sativa, Z. mays and S. lycopersicum, but little in Gossypium. Here we identified 19, 18 and 33 candidate COBL genes from three sequenced cotton species, diploid cotton G. raimondii, G. arboreum and tetraploid cotton G. hirsutum acc. TM-1, respectively. These COBL members were anchored onto 10 chromosomes in G. raimondii and could be divided into two subgroups. Expression patterns of COBL genes showed highly developmental and spatial regulation in G. hirsutum acc. TM-1. Of them, GhCOBL9 and GhCOBL13 were preferentially expressed at the secondary cell wall stage of fiber development and had significantly co-upregulated expression with cellulose synthase genes GhCESA4, GhCESA7 and GhCESA8. Besides, GhCOBL9 Dt and GhCOBL13 Dt were co-localized with previously reported cotton fiber quality quantitative trait loci (QTLs) and the favorable allele types of GhCOBL9 Dt had significantly positive correlations with fiber quality traits, indicating that these two genes might play an important role in fiber development.
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Affiliation(s)
- Erli Niu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - Xiaoguang Shang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - Chaoze Cheng
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - Jianghao Bao
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - Yanda Zeng
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - Caiping Cai
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - Xiongming Du
- State Key Laboratory of Cotton Biology, Cotton Research Institute, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Wangzhen Guo
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Hybrid Cotton R & D Engineering Research Center, Ministry of Education, Nanjing Agricultural University, Nanjing, Jiangsu, China
- * E-mail:
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Nie X, Tu J, Wang B, Zhou X, Lin Z. A BIL Population Derived from G. hirsutum and G. barbadense Provides a Resource for Cotton Genetics and Breeding. PLoS One 2015; 10:e0141064. [PMID: 26517274 PMCID: PMC4627741 DOI: 10.1371/journal.pone.0141064] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2015] [Accepted: 10/05/2015] [Indexed: 11/19/2022] Open
Abstract
To provide a resource for cotton genetics and breeding, an interspecific hybridization between Gossypium hirsutum cv. Emian22 and G. barbadense acc. 3–79 was made. A population of 54 BILs (backcross inbred lines, BC1F8) was developed with the aim of transferring G. barbadense genes into G. hirsutum in order to genetically analyze these genes’ function in a G. hirsutum background and create new germplasms for breeding. Preliminary investigation of the morphological traits showed that the BILs had diverse variations in plant architecture, seed size, and fuzz color; the related traits of yield and fiber quality evaluated in 4 environments also showed abundant phenotypic variation. In order to explore the molecular diversity of the BIL population, 446 SSR markers selected at an average genetic distance of 10 cM from our interspecific linkage map were used to genotype the BIL population. A total of 393 polymorphic loci accounting for 84.4% MAF (major allele frequency) > 0.05 and 922 allele loci were detected, and the Shannon diversity index (I) was 0.417 per locus. The average introgression segment length was 16.24 cM, and an average of 29.53 segments were introgressed in each BIL line with an average background recovery of 79.8%. QTL mapping revealed 58 QTL associated with fiber quality and yield traits, and 47 favored alleles derived from the donor parent were discovered. This study demonstrated that the interspecific BIL population was enriched with much phenotypic and molecular variation which could be a resource for cotton genetics and breeding.
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Affiliation(s)
- Xinhui Nie
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Jianli Tu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Bin Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Xiaofeng Zhou
- Cotton Institute, Xinjiang Academy of Agriculture and Reclamation Science, Shihezi, 832000, Xinjiang, China
- * E-mail: (ZL); (XZ)
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
- * E-mail: (ZL); (XZ)
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Wang H, Huang C, Guo H, Li X, Zhao W, Dai B, Yan Z, Lin Z. QTL Mapping for Fiber and Yield Traits in Upland Cotton under Multiple Environments. PLoS One 2015; 10:e0130742. [PMID: 26110526 PMCID: PMC4481505 DOI: 10.1371/journal.pone.0130742] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Accepted: 05/24/2015] [Indexed: 01/30/2023] Open
Abstract
A population of 178 recombinant inbred lines (RILs) was developed using a single seed descendant from a cross between G. hirsutum. acc DH962 and G. hirsutum. cv Jimian5, was used to construct a genetic map and to map QTL for fiber and yield traits. A total of 644 polymorphic loci were used to construct a final genetic map, containing 616 loci and spanning 2016.44 cM, with an average of 3.27 cM between adjacent markers. Statistical analysis revealed that segregation distortion in the intraspecific population was more serious than that in the interspecific population. The RIL population and the two parents were phenotyped under 8 environments (two locations, six years), revealing a total of 134 QTL, including 64 for fiber qualities and 70 for yield components, independently detected in seven environments, explaining 4.40-15.28% of phenotypic variation (PV). Among the 134 QTL, 9 common QTL were detected in more than one environment, and 22 QTL and 19 new QTL were detected in combined analysis (E9). A total of 26 QTL hotspot regions were observed on 13 chromosomes and 2 larger linkage groups, and some QTL clusters related to fiber qualities or yield components were also observed. The results obtained in the present study suggested that to map accurate QTL in crops with larger plant types, such as cotton, phenotyping under multiple environments is necessary to effectively apply the obtained results in molecular marker-assisted selection breeding and QTL cloning.
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Affiliation(s)
- Hantao Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University. Wuhan 430070, Hubei, China
| | - Cong Huang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University. Wuhan 430070, Hubei, China
| | - Huanle Guo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University. Wuhan 430070, Hubei, China
| | - Ximei Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University. Wuhan 430070, Hubei, China
| | - Wenxia Zhao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University. Wuhan 430070, Hubei, China
| | - Baosheng Dai
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University. Wuhan 430070, Hubei, China
| | - Zhenhua Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University. Wuhan 430070, Hubei, China
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University. Wuhan 430070, Hubei, China
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Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations. Mol Genet Genomics 2015. [PMID: 25758743 DOI: 10.1007/s00438‐015‐1021‐y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
KEY MESSAGE A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.
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47
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Said JI, Knapka JA, Song M, Zhang J. Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations. Mol Genet Genomics 2015; 290:1615-25. [PMID: 25758743 DOI: 10.1007/s00438-015-1021-y] [Citation(s) in RCA: 83] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2014] [Accepted: 02/24/2015] [Indexed: 11/29/2022]
Abstract
KEY MESSAGE A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.
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Affiliation(s)
- Joseph I Said
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, USA,
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Hinze LL, Fang DD, Gore MA, Scheffler BE, Yu JZ, Frelichowski J, Percy RG. Molecular characterization of the Gossypium Diversity Reference Set of the US National Cotton Germplasm Collection. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:313-327. [PMID: 25431191 DOI: 10.1007/s00122-014-2431-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2013] [Accepted: 11/14/2014] [Indexed: 06/04/2023]
Abstract
A core marker set containing markers developed to be informative within a single commercial cotton species can elucidate diversity structure within a multi-species subset of the Gossypium germplasm collection. An understanding of the genetic diversity of cotton (Gossypium spp.) as represented in the US National Cotton Germplasm Collection is essential to develop strategies for collecting, conserving, and utilizing these germplasm resources. The US collection is one of the largest world collections and includes not only accessions with improved yield and fiber quality within cultivated species, but also accessions possessing sources of abiotic and biotic stress resistance often found in wild species. We evaluated the genetic diversity of a subset of 272 diploid and 1,984 tetraploid accessions in the collection (designated the Gossypium Diversity Reference Set) using a core set of 105 microsatellite markers. Utility of the core set of markers in differentiating intra-genome variation was much greater in commercial tetraploid genomes (99.7 % polymorphic bands) than in wild diploid genomes (72.7 % polymorphic bands), and may have been influenced by pre-selection of markers for effectiveness in the commercial species. Principal coordinate analyses revealed that the marker set differentiated interspecific variation among tetraploid species, but was only capable of partially differentiating among species and genomes of the wild diploids. Putative species-specific marker bands in G. hirsutum (73) and G. barbadense (81) were identified that could be used for qualitative identification of misclassifications, redundancies, and introgression within commercial tetraploid species. The results of this broad-scale molecular characterization are essential to the management and conservation of the collection and provide insight and guidance in the use of the collection by the cotton research community in their cotton improvement efforts.
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Affiliation(s)
- Lori L Hinze
- Crop Germplasm Research Unit, Southern Plains Agricultural Research Center, USDA-ARS, College Station, TX, USA
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Qin H, Chen M, Yi X, Bie S, Zhang C, Zhang Y, Lan J, Meng Y, Yuan Y, Jiao C. Identification of associated SSR markers for yield component and fiber quality traits based on frame map and Upland cotton collections. PLoS One 2015; 10:e0118073. [PMID: 25635680 PMCID: PMC4311988 DOI: 10.1371/journal.pone.0118073] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2014] [Accepted: 01/04/2015] [Indexed: 11/19/2022] Open
Abstract
Detecting QTLs (quantitative trait loci) that enhance cotton yield and fiber quality traits and accelerate breeding has been the focus of many cotton breeders. In the present study, 359 SSR (simple sequence repeat) markers were used for the association mapping of 241 Upland cotton collections. A total of 333 markers, representing 733 polymorphic loci, were detected. The average linkage disequilibrium (LD) decay distances were 8.58 cM (r2 > 0.1) and 5.76 cM (r2 > 0.2). 241 collections were arranged into two subgroups using STRUCTURE software. Mixed linear modeling (MLM) methods (with population structure (Q) and relative kinship matrix (K)) were applied to analyze four phenotypic datasets obtained from four environments (two different locations and two years). Forty-six markers associated with the number of bolls per plant (NB), boll weight (BW), lint percentage (LP), fiber length (FL), fiber strength (FS) and fiber micornaire value (FM) were repeatedly detected in at least two environments. Of 46 associated markers, 32 were identified as new association markers, and 14 had been previously reported in the literature. Nine association markers were near QTLs (at a distance of less than 1-2 LD decay on the reference map) that had been previously described. These results provide new useful markers for marker-assisted selection in breeding programs and new insights for understanding the genetic basis of Upland cotton yields and fiber quality traits at the whole-genome level.
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Affiliation(s)
- Hongde Qin
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
- Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China
| | - Min Chen
- Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China
| | - Xianda Yi
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
- Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China
| | - Shu Bie
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
- Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China
| | - Cheng Zhang
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
- Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China
| | - Youchang Zhang
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
- Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China
| | - Jiayang Lan
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
- Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China
| | - Yanyan Meng
- Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
- Key Laboratory of Cotton Biology and Breeding in the Middle Reaches of the Changjiang River (Wuhan), Ministry of Agriculture, Wuhan, P. R. China
| | - Youlu Yuan
- Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyan, China
| | - Chunhai Jiao
- Hubei Academy of Agricultural Sciences, Wuhan, China
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50
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Said JI, Song M, Wang H, Lin Z, Zhang X, Fang DD, Zhang J. A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. Mol Genet Genomics 2014; 290:1003-25. [PMID: 25501533 DOI: 10.1007/s00438-014-0963-9] [Citation(s) in RCA: 133] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2014] [Accepted: 11/18/2014] [Indexed: 12/16/2022]
Abstract
KEY MESSAGE Based on 1075 and 1059 QTL from intraspecific Upland and interspecific Upland × Pima populations, respectively, the identification of QTL clusters and hotspots provides a useful resource for cotton breeding. Mapping of quantitative trait loci (QTL) is a pre-requisite of marker-assisted selection for crop yield and quality. Recent meta-analysis of QTL in tetraploid cotton (Gossypium spp.) has identified regions of the genome with high concentrations of QTL for various traits called clusters and specific trait QTL called hotspots or meta-QTL (mQTL). However, the meta-analysis included all population types of Gossypium mixing both intraspecific G. hirsutum and interspecific G. hirsutum × G. barbadense populations. This study used 1,075 QTL from 58 publications on intraspecific G. hirsutum and 1,059 QTL from 30 publications on G. hirsutum × G. barbadense populations to perform a comprehensive comparative analysis of QTL clusters and hotspots between the two populations for yield, fiber and seed quality, and biotic and abiotic stress tolerance. QTL hotspots were further analyzed for mQTL within the hotspots using Biomercator V3 software. The ratio of QTL between the two population types was proportional yet differences in hotspot type and placement were observed between the two population types. However, on some chromosomes QTL clusters and hotspots were similar between the two populations. This shows that there are some universal QTL regions in the cultivated tetraploid cotton which remain consistent and some regions which differ between population types. This study for the first time elucidates the similarities and differences in QTL clusters and hotspots between intraspecific and interspecific populations, providing an important resource to cotton breeding programs in marker-assisted selection .
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Affiliation(s)
- Joseph I Said
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, USA,
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